A terrible thing happened on the night of January 29th in Washington DC, within view of our Nation’s capital. A U.S. Army Blackhawk helicopter collided with an American Eagle Regional Jet over the Potomac river, killing all 67 people aboard both aircraft.

Any loss of life is a terrible thing, but this specific accident is very disturbing for me because as a licensed commercial pilot and flight instructor with multi-engine and instrument ratings, and being CEO of an aviation technology company, I know that technology is available that could have prevented this accident.

Why wasn’t it being used? Some of it was…but not ALL of it and not EVERYWHERE. It may be shocking to know that our current approach to regulations and policy is that it usually does not change until something like this happens. In parallel, subtle exceptions to rules creep in from a variety of sources over time. We are left with a largely safe system, but one that has various ‘gaps’. While these ‘gaps’ might be small, when they line up, catastrophic events can occur, like this collision.

Below is a map image that illustrates the path of the American Eagle Regional Jet. This path is consistent with a visual approach to runway 33 at Reagan National Airport. This approach is often used for regional jets because they can use the shorter runway (Runway 33), allowing controllers to more efficiently move traffic on Runway 1 (the primary runway) as well as the ramp areas. uAvionix systems are able to track this data using Automatic Dependent Surveillance-Broadcast (ADS-B). Put simply, ADS-B is a way for an aircraft to share its own position (referred to as Ownship) with air traffic control and other aircraft in the area. It shares this information over a radio signal that broadcasts every 1 sec (referred to as 1 Hertz (Hz). In the USA, all commercial and private aircraft are required by regulation to transmit ADS-B position when in specific classes (areas) of the National Airspace (NAS). The DC airspace is one of those areas, so the airliner was compliant and was transmitting ADS-B, as you can see in the image. Notice the helicopter’s path is not illustrated. That is because the Blackhawk helicopter, being a military aircraft, is not required to broadcast ADS-B (nor is it required to receive ADS-B), and as such, is not picked up by ADS-B receivers.

Also required in this class of airspace is a device known as a transponder. A transponder responds to a radio frequency signal (referred to as an interrogation, usually emitted by a ground based radar) and returns data about the aircraft’s type, callsign and altitude as measured by equipment on the aircraft. This allows air traffic controllers to receive higher quality altitude data about each aircraft than the radar itself can provide (most radars only return bearing and range information). In the case of this accident, both aircraft were equipped with transponders and both transponders were sharing position information. The image below shows the transponder tracks for each aircraft.

In addition to ADS-B and transponders, all transport category aircraft operated under Part 121 of the FAA regulations (14 CFR 121) are also required to have a system called Traffic Collision Avoidance System (TCAS) aboard. TCAS uses the transponders on each aircraft to query other aircraft’s transponders to determine if they are on a collision course. If the systems determine they are on a collision course, warnings and commands are issued to the flight crew from the TCAS. These are known as Traffic Advisories (TA) and Resolution Advisories (RA). A TA is for awareness only, but an RA is a command that must be followed by the crew immediately.

So why didn’t the TCAS tell the American Airlines crew to do something? Well, the airport environment is a busy place with aircraft operating very near each other. Further, the final approach segment for a flight crew is a high workload time of flight. Since the TCAS would likely trigger a large number of TA’s and the potential for false RA’s at low altitude, it is suppressed below 1,000 feet above ground level (AGL). Specifically, there are no RA’s issued below 1,000 feet AGL, and all TA’s are muted below 500 feet AGL.  This accident occurred at roughly 300 feet AGL.

The U.S. Army Blackhawk Helicopter is not required to have TCAS aboard, and even if it did, it would have been suppressed just as the American Airlines jet’s was.

This is point #1 – in this type of airspace with this volume and proximity of traffic, why are all aircraft not required to use all available technology to avoid collision?

To address that, we must look at how aircraft are typically separated by pilots and air traffic control.

The last line of defense against mid-air collision is the human eyeball. The regulations (14 CFR 91.113) clearly spell out that it is the pilot’s responsibility to ‘see and avoid’ all other aircraft to avoid a collision.  Most general aviation operations rely on this method to avoid collisions as most of the country is not covered by radar or managed by air traffic control. There are strategic and tactical operations that we use to minimize the chances of a mid-air collision – things like specific traffic patterns, cruising altitudes, right of way rules, radio calls – but at the end of the day, it is a human pilot looking out the window that is the last line of defense.

Air traffic control exists to assist the pilot with that task by deploying a variety of techniques and technologies ranging from calling out the position of other aircraft, to tracking aircraft on radar to issuing heading and altitude commands to pilots to help them navigate away from potential collisions.  Controllers talk to pilots over good ol’ radios.  Simplex radios, to be specific. Simplex means that only one person can broadcast at a time, and if two people key the microphone at the same time, they will cancel each other out (we call this getting ‘stepped on’). To help alleviate that risk, specific frequencies are used in different sectors of airspace, and the community uses a specific syntax, cadence and sequence of communication to minimize ‘two talking at once’. The system works remarkably well.  Additionally, when all the pilots in a specific area are on the same frequency, we can all hear the communications between ATC and the other aircraft, allowing us each to form a mental picture of the aircraft in the airspace (something we call situational awareness, or SA).

So what happened in DC?  Both aircraft WERE in communication with air traffic control, but they were NOT on the same frequency. Military aircraft use Ultra High Frequency (UHF) radios and civilian aircraft use Very High Frequency (VHF) radios. The helicopter and the airliner could not hear each other, nor could they hear what the controller was saying to the other aircraft. That is to say that the respective crew’s ability to build a mental picture of the airspace and aircraft in it was limited.

Additionally, when the weather conditions are clear, it is routine practice for a controller to call out traffic to a crew, something like “American 2135, traffic 12 o’clock and 4 miles is a United Boeing 737, report that traffic in sight”. If the crew responds saying they see the traffic, the controller can then direct the crew to ‘maintain visual separation’ with that traffic, effectively handing off the accountability for separation to the flight crew. It seems this happened properly on the night of the collision, with the controller calling out the airliner’s position to the helicopter crew and the helicopter crew acknowledging they had the traffic in sight. But there is a wrinkle in this…did the helicopter crew have the SAME aircraft in sight that the controller was calling out? If you look at the geometry of the aircraft just prior to the collision, there were likely TWO airliners within the field of view of the Blackhawk crew – the one they eventually collided with and a different airliner that was on final approach to a different runway at DCA much farther away. IF the Blackhawk crew looked up when the traffic was called and happened to see the more distant aircraft first, they MIGHT have acknowledged the controller that they had the aircraft in sight, but it was the wrong aircraft. This situation is demonstrated in the image below and a 3D model describes the view in this Washington Post article, (Washington Post – 3D Model of DC Plane Crash):

Put simply, if both aircraft were transmitting and receiving ADS-B, they would have likely both been aware of each other’s position in plenty of time to avert a collision. In our opinion, the only reason ADS-B equipage is not mandatory for ALL aircraft is that there have been too many opposing voices in our country, citing reasons like privacy, government overwatch, frequency and system saturation, etc. Those voices have been successful in ‘carving out’ specific exceptions to the rule the FAA enacted in 2020, mandating the use of ADS-B Out in specific classes of airspace for just about all types of aircraft, except military, law enforcement and some other special cases. Outside of those classes of airspace, ADS-B Out (or In) is not required.

In partnership with a Boeing subsidiary called ForeFlight, uAvionix manufactures and sells a device called a Sentry. It is a portable device that contains sensors and receivers that provide a pilot with their position, attitude and receipt of ADS-B data, which contains both weather information and traffic information. It connects wirelessly to Apple and Android devices allowing for traffic and weather data to be shown on a moving map in the cockpit. In the case of the DC mid-air, this device, if it were used on the Blackhawk helicopter, would have alerted the crew to the presence of the airliner (since the airliner was transmitting ADS-B), and potentially could have mitigated this disaster.

So there are a bunch of ‘Yes, IF’s…’ here:

• IF the Blackhawk helicopter had a Sentry and an iPad running ForeFlight, they would have been alerted to the airliner.
• IF the Blackhawk helicopter was broadcasting ADS-B, the airliner would have been alerted.
• IF both aircraft were talking to tower on the same frequency, they would have been more aware of each other’s position.
• IF we did not rely on human eyesight for the safe separation of aircraft…
• IF instead of a set of exceptions to rules, we had mandatory equipage of position reporting technology for ALL aircraft…

I resonate deeply with our company’s ‘why’ of radically innovating to make the skies open and safe for all. We have done the innovation part, and we continue to do so, aligned with this mission. It is sad and frustrating when I know we have the means to avoid these types of tragedies, but special cases and exceptions preclude those technologies from getting deployed. Nevertheless, this event strengthens our resolve to get our capabilities into the field to prevent this type of accident in the future. I firmly believe we not only have the technology to address these challenges, but that we can also assuage the concerns of those who have objections to the technologies in a positive way so that no one ever has to lose a loved one to a mid-air collision ever again.

The post Mitigating Mid-Air Collisions: The Reagan Mid-Air appeared first on Inside GNSS - Global Navigation Satellite Systems Engineering, Policy, and Design.

THIERRY AUTHIÉ, GUILLAUME COMELLI, SÉBASTIEN TRILLES, THALES ALENIA SPACE, TOULOUSE, FRANCE BYUNGSEOK LEE, MINHYUK SON, KOREA AEROSPACE RESEARCH INSTITUTE, REPUBLIC OF KOREA CHEON SIG SIN, ELECTRONICS AND TELECOMMUNICATION RESEARCH INSTITUTE, REPUBLIC OF KOREA

The Korean Augmentation Satellite System (KASS) is a satellite-based augmentation system (SBAS) developed by the Republic of Korea (South Korea) to augment the functionality of the Global Positioning System (GPS) in the Korean Peninsula and the surrounding regions. KASS was designed to enhance the accuracy and reliability of GPS signals within the country. In aviation, it enables more precise and reliable navigation for aircraft, supporting instrument approach procedures and improving operational efficiency.

A SBAS is a Global Navigation Satellite System (GNSS) augmentation system standardized in the International Convention on Civil Aviation SARPS Annex 10 [1], Volume 1, published and maintained by the International Civil Aviation Organization (ICAO). KASS provides safety-critical services for civil aviation, up to Approach with Vertical Guidance 1 (APV I ) service level, as well as an open service usable by other forms of transportation and possibly other position, navigation and timing (PNT) applications.

The KASS system provides improved GNSS navigation services for suitably equipped users in the agreed service areas of the Republic of Korea by broadcasting an augmentation signal of the GPS Standard Positioning Service (SPS).

To ensure the smooth operation of the system, KASS includes a network of ground receiver stations dedicated to collecting GPS measurements, a set of ground processing stations responsible for monitoring and controlling the satellites, and a set of ground uplink stations managing the transmitted signals toward two Geostationary Earth Orbiting (GEO) satellites. These ground control stations accurately calculate the orbit and clock information of the satellites, as well as the mono frequency L1 ionosphere delay, and continuously update the transmitted signals accordingly.

One of the system’s key features is its ability to enhance the integrity and reliability of positioning information. KASS incorporates integrity monitoring functions to detect and alert users of any potential errors or anomalies in the GPS signals. This is crucial for safety-critical applications that require precise positioning data, such as aviation and maritime navigation.

The augmentation signal provides corrections of GPS satellites orbits and clocks and integrity bounds of orbit/clock residual errors, as well as corrections and integrity bounds for ionosphere delays. The KASS satellites transmit signals that are compatible with GPS, allowing KASS-capable receivers to seamlessly switch between GPS and KASS signals and to compute a navigation solution with greater accuracy.

The KASS system qualification was achieved by December 15, 2023, and safety of life aeronautical services have been fully operational since December 28, 2023. 

The current network of KASS Reference Stations (KRS) is composed of seven KRS sites all deployed on the Republic of South Korea land masses. Each KRS includes two independent channels based on NovAtel WAAS GIII receivers that provide GPS signal tracking and measurements. This concentrated network allows users to reach APV I service level but not more stringent service levels like the Category 1 (CAT 1) approach.

This article presents an analysis of a system upgrade to reach the CAT I service level based on representative synthetic data scenario. This analysis involves an extension of the KRS network and minor changes in the navigation algorithms.

KASS Services and Architecture

KASS is designed to provide performance-based navigation (PBN) aeronautical procedures, such as RNAV or RNP approaches, enable aircraft to fly along precise paths during departure, enroute and approach phases. PBN is a modern concept in aviation that uses satellite-based navigation technology and proposes a set of procedures that enhance operating efficiency, reduce flight distances, improve airspace capacity and enhance safety.

The KASS system is designed to ensure four safety critical service levels:

• Enroute continental over the Incheon FIR area. Flight segments after arrival at initial cruise altitude until the start of descent to the destination.

• Enroute terminal over the Incheon FIR area for descent from cruise to Initial Approach Fix. 

• NPA over the Incheon FIR area. For non-precision approaches in aviation, this instrument approach and landing uses lateral guidance but not vertical guidance.

• APV I over South Korea landmasses (including Jeju Island) for precision approaches with vertical guidance.

KASS will provide open service over Incheon FIR area. 

Figure 1 shows the KASS service areas.

The KASS system is designed to be a system-of-systems ensuring the following main functions [2-3]:

• Collect GPS data at various locations in the Republic of Korea (and possibly other states in the future) through Korea Receiver Stations (KRS).

• Compute corrections and associated integrity bounds from ranging measurements of GPS satellites in view of KASS, and format messages compliant with the SBAS user interface standardized in ICAO SARPS Annex 10 [1] and the RTCA MOPS 229-D Change 1 [4]. This function is ensured by the Korean Processing Stations (KPS).

• Uplink a signal carrying these messages to navigation payloads on the KASS GEOs with Korean Uplink Stations (KUS).

• Broadcast the signal to users after frequency-conversion to the L1 band.

The KPS is the core component of the KASS system responsible for computing orbit, clock, ionosphere corrections, and alert information below the Navigation Overlay Frame (NOF). It uses data from a set of reference stations, the KRS, to perform these calculations. The KPS consists of two independent elements known as the processing set (PS) and the check set (CS).

The PS is responsible for computing the complete navigation context for the GNSS constellation, including orbits, clocks and the ionosphere model. It then prepares and sends the NOF, which is broadcasted to users. The CS acts as a supervisory entity by applying the NOF to GPS messages, ensuring consistency with an independent set of measurements to maintain integrity and control.

The KPS-PS component plays a critical role in achieving high-performance levels, specifically for the APV I service level. APV I is a type of PBN approach that provides lateral and vertical guidance to aircraft during the approach and landing phase. APV I approaches typically use satellite-based augmentation systems like the Wide Area Augmentation System (WAAS), the European Geostationary Navigation Overlay Service (EGNOS) and now the Korean Augmentation Satellite System (KASS). These approaches provide accurate lateral and vertical guidance, allowing pilots to perform precision approaches with reduced reliance on ground-based navigational aids.

From APV I to CAT I Aviation Service for KASS

CAT I (localizer performance with vertical guidance 200) is another type of PBN approach that offers even higher precision and accuracy than APV I. CAT I approaches also use satellite-based augmentation systems like WAAS or EGNOS. With CAT I, the lateral and vertical guidance is provided by the aircraft’s flight management system, enabling pilots to fly approach paths that closely resemble traditional instrument landing system (ILS) approaches. CAT I approaches can provide the same level of guidance and minimums as Category I ILS approaches, with decision heights as low as 200 feet above the runway.

Both APV I and CAT I approaches provide increased flexibility, safety and efficiency compared to traditional ground-based navigation systems. They allow for greater access to airports in various weather conditions, reduce reliance on infrastructure, and enable more precise and efficient aircraft operations. These approaches have become increasingly popular and are being implemented worldwide to enhance flight safety and optimize airspace use.

Performance of a satellite navigation system can be expressed through Five Criteria: accuracy, integrity, continuity, availability and time-to-alert (TTA). The overall detailed performance specifications are depicted in Table 1.

Accuracy is the difference between the computed value and the actual value of the user position and time. Usually, accuracy is defined as the 95th percentile of the positioning error distribution.

The system TTA is defined as the time starting when an alarm condition occurs to the time the alarm is displayed in the cockpit. Time to detect the alarm condition is included as a component of integrity.

The alert limits are the maximum allowable error in the user position solution before an alarm is to be raised within the specific time to alert. This alert limit is dependent on the flight phase, and each user is responsible for determining its own integrity in regard to this limit for a given operation phase following the information provided by the SBAS SIS.

The integrity risk is the probability during the period of operation that an error, whatever the source, might result in a computed position error exceeding a maximum allowed value, called alert limit, and the user not be informed within the specific time to alert.

To display the integrity of the satellite corrections for each GPS satellite, the UDRE Safety Index is used to assess the integrity margin. The UDRE Safety Index is defined as the ratio . The Satellite Residual Error for the worst user location (SREW) was computed as the pseudorange error projection due to the remaining satellite ephemeris and clock errors, after KASS corrections were applied for the worst user location of the relevant service area. The relevant service area corresponds to the intersection of the service area and of the monitored satellite footprint.

Also, to display the integrity of the ionosphere corrections for each IGP, the notion of Grid Ionosphere Vertical Error (GIVE) Safety Index is used. The GIVE Safety Index is defined as the ratio , with the GIVE Error defined as the vertical pseudorange error at the considered IGP location due to the remaining ionospheric delay after applying the GIVE corrections.

Continuity defines the ability of a system to perform its function without interruption during the operation planned by the user (for example landing phase of an aircraft). It is evaluated as the probability that from the moment when the criteria of precision and integrity are completed at the beginning of an operation, they remain so for the duration of the operation.

Availability is the percentage of time when, over a certain geographical area, the criteria of accuracy, integrity and continuity are met.

Finally, the service area is the geographic zone where the SBAS shall provide service availability.

As depicted in Table 1, the major difference between CAT I and APV I is more demanding requirements in terms of vertical alarm limit and TTA, resulting in a reduction from 50m to 35m for the vertical protection level and from 10s to 6s for TTA.

The KASS system is designed according to the same architectural principles as the European EGNOS system, which complies with the CAT I service requirements concerning TTA. Therefore, all the elements justifying the TTA performance developed for the EGNOS system apply to the KASS system without any restrictions. This aspect is thus not considered a difficulty.

The main challenge in achieving the CAT I service level concerns the domain of vertical protection volume. Currently, KASS is compliant to APV I precision approach procedure but is limited for the achievement of CAT I service level due to the impact of ionosphere error estimation. With the low number of available measurements from only seven collocated stations, it results in very high integrity bounds (GIVE), which directly affects protection volumes in the vertical direction.

To overcome the limitation of the available measurement volume using only the contributions from the GNSS system, two steps are being considered.

The first step is to include new observables by incorporating measurements from the Galileo constellation into the ionosphere estimation algorithms. It should be noted that Galileo measurements are not incorporated into other navigation algorithms, meaning the system does not monitor the Galileo constellation or calculate any orbit or clock corrections for it.

The second step is to add stations outside of Korea, which would provide better observability in both the dynamics of ionosphere activity and orbit estimation. This addition of external stations would enhance the overall measurement coverage and improve the accuracy of the estimation process.

For all these assessments, fault-free synthetic data are used (analyzed September 3-5, 2002), allowing a first level of performance the KASS system may reach for the provision of CAT I approach service. The results are produced with the same set of KPS navigation algorithms.

CAT I Performances Reached with Introduction of Galileo 

The first extended configuration considers the introduction of Galileo measurements and the current KASS reference station network.

The simulations is realized with:

• Seven reference stations (Yangju, Gwangju, Jeju AP, Jeju TS, Yeongdo, Dodong and Yangyang).

• 27 GPS: for satellites and ionosphere monitoring.

• 24 Galileo: for ionosphere monitoring only.

The different cases presented indicate the availability of CAT I by monitoring the satellites from a minimum elevation angle of 5° with at least one station in the network, then at 10° and 15°.

This experimentation shows CAT I service level can be reached by introducing more observables for the ionosphere monitoring. Indeed, the availability at 99% is reached with the constraint of satellites monitored from 5° elevation by one station. 

First, these new measurements enrich the internal ionosphere model and then contribute to reduce the ionosphere correction errors.

However, because of the direct impact of the integrity bounds on the calculation of protection volumes, the most visible impact of these new measurements on achieving availability is their contribution to reducing GIVE at each Ionosphere Grid Point. 

Second, we observe a clear and direct dependence between the availability of CAT I service level and the minimum angle of satellite monitoring. This phenomenon is the result of waveform deformation (EWF for Evil Wave Form) processing in navigation algorithms, which requires at least one multi-correlator station to lock onto a satellite.

In all maps the integrity target is held with a good margin:

• The maximum satellite Safety Index is 0.77.

• The maximum Ionospheric Grid Point Safety Index is 0.76.

• Integrity is ensured as long as the Safety Index is below 5.33.

Focusing on the Incheon Airport location [127° E;37° N], Figure 3 shows performance in terms of position error and protection levels achieved for Sept. 4, 2022.

The VPL evolves mainly between 15m and 30m, except for a few minutes where it goes above the alarm limit of 35m. The HPL always remain below 30m. 

CAT I Performances Reached with Reference Station Extension (Large Network)

The second extended configuration considers the introduction of Galileo measurements and additional reference stations located outside South Korea landmass to build a large station network.

The added KASS reference stations are depicted in Figure 4.
Five new references stations are considered: Ulaanbaatar (Mongolia), New Delhi (India), Perth (Australia), Wellington (New Zealand) and Hawaii.

The simulation is performed with:

• 12 reference stations.

• 27 GPS: for satellites and ionosphere monitoring.

• 24 Galileo: for ionosphere monitoring only.

Figure 5 shows the availability performance results with satellite monitoring performed using measurements at a minimum of 15° elevation. 

• Again, in all maps, the integrity target is held with a good margin.

• The maximum satellite Safety Index is 0.92.

• The maximum Ionospheric Grid Point Safety Index is 1.33.

In this case, CAT I availability performance is improved with 12 stations. The effect is not on the reduction of integrity value (GIVE) regarding the ionosphere, as the additional five stations are too far away to have an impact. However, having remote stations allows for much better satellite monitoring. This is clearly visible in Figure 6. 

Because satellites are monitored much earlier with 12 stations, the effect of EWF monitoring becomes negligible by removing satellites if they are not seen by at least one station at more than 10° or 15°. As soon as a satellite becomes visible in the service area, there is always a remote station that can see the satellite with a good elevation.

However, EWF monitoring has a noticeable effect in the case with seven KRS, where the availability decreases as the minimum angle increases.

Focusing on Incheon Airport location [127° E;37° N], Figure 7 shows performance in position error and protection levels achieved on September 4, 2002.

This approach has also high interest in the frame of geographical extension of KASS service, for instance the APV I coverage is extended. Table 2 shows the comparison between the APV I availability with the seven KRS and 12 KRS networks.

Again, in all maps the integrity target is held with a good margin:

• The maximum satellite Safety Index is 0.92.

• The maximum Ionospheric Grid Point Safety Index is 1.33.

CAT I Performances Reached with Reference Station Extension (Narrow Network)

The third extended configuration considers the introduction of Galileo measurements and additional reference stations located outside the South Korea landmass to build a narrow station network.

Added KASS reference stations are depicted in Figure 8. Five new reference stations are considered: Shangai, Dalian, Mudanjiang (China), Izumo and Goto Tsubaki (Japan).

Figure 9 shows the availability performance results with a satellite monitoring performed using measurements with a minimum of 15° elevation. 

Here again, in all maps the integrity target is held with a good margin:

• The maximum satellite Safety Index is 0.87.

• The maximum Ionospheric Grid Point Safety Index is 0.85.

Focusing on the Incheon Airport location [127° E;37° N], Figure 10 shows the performances achieved on Sept. 4, 2002.

Much like the previous cases, the VPL remains around 15 to 25m, except for a spike around 5 p.m. The HPL remains around 10m the entire day. The narrow network extension has a benefit aspect on the navigation error NSE, mainly because of better ionosphere corrections accuracy.

Conclusion

The experimentation shows the KASS system evolution makes it possible to achieve the CAT I operational approach. The system’s adherence to architectural principles warrant its ability to meet the TTA requirements. Leveraging the Galileo system, the introduction of new GNSS measurements with the unchanged KRS network results reduces ionosphere integrity bounds, further enhancing the legacy system’s overall availability below the vertical alert limit compatible to CAT I. The study has also envisaged the addition of new external reference stations whose results have established a significant impact on satellite monitoring. With these new adjunctions, the KASS system would improve its capabilities to provide effective and accurate positioning services, proposing for safer and more efficient navigation in the CAT I operational approach.

References 

(1) “Standards and Recommended Practices (SARPS) Annex 10 to the Convention on International Civil Aviation,” Volume I, up to Amendment 86, July 2006, ICAO (International Civil Aviation Organization). 

(2) Houllier, Carolle, Authié, Thierry, Comelli, Guillaume, Lee, ByungSeok, Lee, Eunsung, Yun, Youngsun, SIN, Cheon Sig, “KASS: The Future of SBAS in Korea.” Inside GNSS, Junary–February 2023, pp 50-57

(3) Thierry Authié, Mickael Dall’Orso, Sébastien Trilles, Heonho Choi, Heesung Kim, Jae-Eun Lee, Eunsung Lee, Gi-Wook Nam, “Performances Monitoring and Analysis for KASS,” In Proc. of ION GNSS+, pp 958–978, 2017

(4) “Minimum Operational Performance Standards (MOPS) for Global Positioning System/Wide Area Augmentation System Airborne Equipment,” RTCA/DO-229D with Change 1, February 1, 2013.

Authors

Thierry Authié is a specialized engineer in space flight dynamics, precise orbit determination and navigation. He received his MS degree in Applied Mathematics from the INSA, Toulouse (France) in 2004. He currently works on SBAS and navigation algorithm at Thales Alenia Space.

Guillaume Comelli
is a system engineer and system architect at Thales Alenia Space. He received his MS degree in electrical engineering from the INSA, Lyon (France) in 1994. He has been the Technical Manager for the KASS program since 2019.

Sébastien Trilles is an expert in orbitography and integrity algorithms at Thales Alenia Space in Toulouse, France. He holds a PhD in Pure Mathematics from the Paul Sabatier University and an advanced MS in Space Technology from ISAE-Supaero. He heads the Performance and Processing Department where high precise algorithms are designed as orbit determination, clock synchronization, time transfer, reference time generation, integrity and ionosphere modelling algorithms for GNSS systems and augmentation.

ByungSeok Lee received a BS degree in electric and electrical engineering, a MS degree and a PhD in electrical and computer engineering from University of Seoul, Seoul, Korea, in 2002, 2009, 2015, respectively. He has conducted research related to a Global Navigation Satellite System (GNSS) including the Satellite Based Augmentation System (SBAS) in Korea Aerospace Research Institute. He was in charge of the KASS program from November 2020 to February 2024. He is currently responsible for the entire KASS operation and maintenance.

Minhyuk Son received his BS and MS degrees in electrical engineering from Daegu University, South Korea, in 2009, and 2011, respectively. He joined the Korea Aerospace Research Institute in 2011 and is currently in charge of operation safety technology development for KASS.

Cheon Sig SIN received a BS degree in electric and electrical engineering from Hanyang University, and a MS degree from Chungnam University, Korea in 1990, 2000 respectively. He conducts research related to a GNSS Signal Interference Detection and Mitigation Technology and Global Navigation Satellite System (GNSS) including the Satellite Based Augmentation System (SBAS) in Electronics and Telecommunication Research Institute. He has been in charge of the GK-3 SBAS Payload Development program since April 2021.

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PAUL ANDERSON, GEORGE SCHMITT, FURQAN AHMED, PATRICK SHANNON, TRUSTPOINT INC.

A 2007 Inside GNSS article examined C-band as a future for GNSS signals, with authors outlining its advantages and disadvantages when compared to L-band in context of the Galileo system and its potential role. Nearly 20 years later, we reexamine the cost/benefit trades for C-band for navigation in the context of the NewSpace economy and future commercial GNSS systems operating in low Earth orbit (LEO). In that time, C-band has become critical for resilient PNT, with TrustPoint beginning to deploy a proliferated LEO constellation of microsatellites broadcasting next-generation navigation signals in the 5010 to 5030 MHz Radionavigation Satellite Service (RNSS) allocation at C-band. TrustPoint’s future LEO GNSS service will enable rapid time-to-first-fix, meter and sub-meter positioning accuracy, improved jamming resistance due to frequency selection, diversity and increased signal strength, and an encrypted, spoof tolerant signal with built-in authentication.

The Paradigm Shift of Commercial GNSS

Over the past 50 years, the U.S. GPS and international GNSS counterparts have provided invaluable services in support of commercial, civil government, and military operations across the globe. Given the crucial role they play, it is difficult to envision a world without the ever-present support of these services streaming down from space. Recent reports estimate the global installed base of GNSS-enabled devices is projected to grow from 5.6 billion units in 2023 to almost 9 billion units across all markets by 2033, with the number of GNSS devices shipped per year increasing from 1.6 billion in 2023 to 2.2 billion units in 2033. As humanity exits the first complete epoch of the information age and boldly leans into the age of autonomy and ubiquitous connectivity, there is an expectation that GNSS-enabled devices will further proliferate and continue integrating more broadly and deeply into our way of life.

While humanity finds tens, if not hundreds, of new applications for GNSS every year, and develops an analogous number of unique receivers, the update rate for the satellite systems and the signals they transmit follow closer to decadal timeframes. This slow rate of technical progress is driven by a variety of factors, including the high costs of government system development, limited spectrum availability, and strict backwards compatibility requirements. Unfortunately, this rate of technical progress is severely outpaced by adversarial activity, new application requirements, and technologies from adjacent markets readily available for integration into the larger GNSS ecosystem. In response to this reality, TrustPoint has architected a responsive, resilient and evolutionary LEO PNT system and signal paradigm that enables rapid service upgrades to achieve receiver forward compatibility.

To date, all space-based PNT systems and services have been funded, owned and operated exclusively by world governments with significant budgets, lengthy schedules, and public Interface Control Documents (ICDs). A new era of space-based alternative PNT (A-PNT) is dawning with the emergence of venture-backed commercial companies seeking to fill capability gaps of heritage GNSS services with new technologies and solutions targeting a $260 billion plus total addressable market in navigation and location-based services enabled by commercial satellite platforms and advancements in microelectronics technology. This is a paradigm shift in that GNSS users will soon have access to commercial “PNT-as-a-Service” in addition to the heritage GNSS systems owned by world governments. Novel A-PNT business models and pricing strategies, proprietary signal ICDs, and service-level agreements specifying signal availability and signal-in-space accuracy will become standard—and this will fundamentally change the way global users subscribe to and access next-generation A-PNT services enabling secure, resilient and high-accuracy time and position solutions.

TrustPoint is deploying a purpose-built, commercial A-PNT service using a proliferated LEO constellation of microsatellites broadcasting next-generation navigation signals in the 5010 to 5030 MHz RNSS allocation at C-band. TrustPoint’s commercial, dual-use LEO PNT system and C-band service will enable rapid time-to-first-fix, meter and sub-meter positioning accuracy, improved jamming resistance due to frequency selection, diversity and increased signal strength, and an encrypted, spoof-tolerant signal with built-in authentication for all users. The solution is made possible by our constellation of low-cost LEO microsatellites that leverage commoditized space platforms, rideshare launch services, and patented innovations in navigation signal generation and processing at the RF physical and navigation data layers, enabling next-generation commercial GNSS services made possible by smaller wavelengths, smaller satellites and smaller orbits.

In this article, we summarize the cost and benefit trades of C-band versus L-band at LEO versus medium Earth Orbit (MEO), inclusive of considerations for space segment design, architecture, and size, weight, power, and cost (SWaP-C); signal and service design; and attenuation effects and path delay. 

Commercial Space Segment Considerations

Why is it that after 50 years of satellite navigation technologies and services, LEO PNT has only become relevant in the past 5 years? The answer could lie in the trifecta of (1) the commoditization of microsatellite platforms spurred by the “NewSpace” ecosystem dominated by commercial players; (2) continued miniaturization of software-defined radios and other analog and digital electronics; and (3) the routine availability of low-cost rideshare launch opportunities to common LEO orbits. TrustPoint is leveraging all three of these factors to enable a commercially-funded space segment that is both affordable and high-capability—a combination that wasn’t possible at the scale needed for a new LEO PNT system even 5 years ago. Proliferated LEO architectures comprised of small-but-capable satellites have been technically, cost-prohibitively, or politically out of reach for First World governments, let alone commercial enterprises seeking to generate revenue from new PNT service offerings. As space technologies within the NewSpace economy have continued to relentlessly evolve on accelerated timelines, bootstrapped by venture capital and driven by new use cases arising from humanity’s increasingly interconnected and autonomous future, it is now possible for a commercial business to pursue—in fact, succeed in—delivering space-based LEO PNT services.

Proliferated LEO Constellation. Design and analysis of proliferated LEO constellations for alternative PNT is well-studied in the literature and may be considered a solved problem, see for example [3, 4,5]. The key consideration with lowering the orbital altitude of a PNT system from GNSS MEO altitudes (19,000 to 24,000 km) down to LEO altitudes (500 to 1,000 km) is the number of satellites required to provide persistent four-in-view (“4-fold”) coverage increases exponentially as the altitude decreases, specifically according to this summary relation for minimum number of satellites:

where K=4 for four-in-view coverage, and θ is the Earth central angle. Assuming a 10° minimum elevation angle for a terrestrial user accessing a LEO constellation at 550 km, θ=15°, which translates to more than 400 satellites required to maintain persistent, global 4-fold coverage at the minimum orbit inclination i_min=90–θ=75 deg. This can be reduced by combining multiple “shells” where each shell is defined as a unique altitude, inclination, number of planes, and number of satellite slots per plane. Heterogeneous combinations of shells can then provide superior coverage properties for PNT applications in terms of common metrics such as 4-fold daily availability, 4-fold recovery time in the event of intermittent outage, and the variants of Dilution of Precision (DOP).

Given the significant number of minimum satellites required for LEO PNT coverage when compared with the order of magnitude fewer satellites used in heritage GNSS constellations, the prudent system architect must trade optimal constellation geometry and coverage properties to improve the system cost and operational considerations. The availability of commoditized rideshare launch opportunities has spurred dramatic reductions in launch cost per kilogram of upmass, but these rideshare launch opportunities target standard Sun-Synchronous and mid-inclination destinations, so cost savings for leveraging rideshare launch are only realized if the operational orbits for the LEO PNT system are “close” to these standard dropoff locations. Higher altitude LEO orbits above 700 km, or non-standard LEO orbits such as elliptical orbits, carry additional requirements for last-mile delivery services via Orbital Transfer Vehicles (OTVs) or expensive dedicated launch services.

In addition, with an increasingly congested space environment, the number of planes, inter-plane phasing, and intra-plane phasing must be carefully considered in light of operational and spaceflight safety constraints, namely (1) access to routine ground station contacts for telemetry, tracking and command (TT&C); (2) routine collision avoidance course of action assessment (arising from both external conjunctions and self-conjunctions amongst satellites in the same LEO constellation); and (3) sufficient end-of-life deorbit to ensure compliance with flowdown regulatory requirements from the cognizant licensing authority. A lack of consideration for any of these items can lead to significantly higher incurred costs for LEO system development, deployment, operation, and sustainment, which are especially critical for commercial entities in the process of developing new LEO PNT systems and services.

The deployment of hundreds of satellites necessarily takes time, so another important consideration is not only the final end-state constellation design, but the roll-out plan for various phases of the constellation deployment, which impacts coverage and system performance over time. At full operational capability (FOC), constellation management pivots from deployment to sustainment, and given that 3 to 5 years of design life is typical for low-cost LEO microsatellites, upwards of 20% of the constellation capacity may need to be replaced on an annual basis, depending on satellite reliability, orbital altitude, space weather conditions, and the solar cycle (which impacts atmospheric density and therefore the rate at which LEO orbits decay due to atmospheric drag). This underscores the importance of minimizing the total cost per satellite delivered to orbit, while maximizing production capacity to ensure routine readiness of replacement batches of satellites that are acceptance tested, flight-ready, and standing by for launch.

Commoditized Microsatellites. The global small satellite market grew from $5.4 billion in 2023 to $6.6 billion in 2024, and is projected to grow to $14 billion by 2028, driven by both NewSpace incumbents and new LEO constellation entrants in the areas of SATCOM, EO/IR imagery, RF sensing, SAR, and PNT [6]. Small satellites comprised 93% of all spacecraft launched from 2014 to 2023, accounting for 41% of total upmass, given the 25x increase in the number of small satellites launched per year from 2014 (115) to 2023 (2,860) [7]. These trends have been enabled by the increasing commoditization of satellite components, subsystems and entire platforms with competitive price points, sub-12-month lead times, and increasing capability densities for performing diverse mission sets. What was once only feasible with a government-class budget and schedules measured in years—or even decades—is now doable for venture-backed commercial startups with small budgets and schedules measured in months.

From 2022 to 2023, TrustPoint reviewed 16 CubeSat-class platforms (3U, 6U and 12U, where 1U is defined as a 10x10x10 cm cube) offered as commercial-off-the-shelf (COTS) products by commercial bus providers both in the U.S. and internationally. These platforms ranged from Technology Readiness Level (TRL)-6 to TRL-9, and were scored based on SWaP available to the payload, ease of integrating a propulsion system, and lead times and unit pricing for various quantities of identical units. For an RF payload, the size and weight can, in general, be optimized, but power consumption is directly related to the duty cycle that is allowable for signal transmission—indeed, “P” is the most challenging dimension of SWaP for a PNT application. As shown in Figure 1, these 16 reviewed CubeSat platforms can be grouped into four categories on the basis of Orbit Average Power (OAP) available to the payload and the unit cost per platform at small quantities. Our survey confirmed strong advancements in CubeSat technologies over the last 3 to 5 years, specifically 2 to 3x increases in OAP available to the payload and 30% to 50% reductions in platform cost. Furthermore, our assessment identified multiple bus providers in the “pack leader” category who are aggressively pushing toward higher capability at a lower price point by means of vertical integration and continuous innovation in bus technology stacks, and preparing parallel production lines and supply chains to enable an additional 20% to 30% unit cost reduction for the large quantities required for fielding a proliferated LEO constellation.

Multiple high-performance CubeSat platforms in the $200,000 to $300,000 range are now available, inasmuch as the PNT payload being integrated with the commercial bus conforms to standard mechanical, electrical and thermal interface requirements. This price point per constellation node is multiple orders of magnitude beneath the price tag of a single GNSS MEO satellite. Given the cost of a single GPS Block III satellite is estimated at $250 million, a $250,000 price point per LEO CubeSat is a 1/1000x reduction that trades the larger available SWaP and 2 to 3x increased design life of a heritage MEO satellite for the dramatically reduced unit cost per commercial LEO microsatellite.

Low SWaP C-Band PNT Payload. Thanks to the realization of Gordon Moore’s (co-founder of Intel) famous 1965 prediction that the number of transistors on microchips would double approximately every two years, the SWaP of commercially available microelectronics has significantly reduced over the past 50 years of satellite navigation technologies. The semiconductor industry has continuously innovated to shrink the size of transistors to fit more onto single microchips, thereby increasing transistor density per integrated circuit and leading to electronics with higher efficiency, increased compute performance, and lower cost per chip. “Moore’s Law” has significantly influenced the miniaturization of software-defined radios over time [9] and has driven significant SWaP reductions and performance increases in foundational microelectronics for mobile phones, GNSS user equipment (Figure 2), and myriad other technologies.

Similarly, the advancements resulting from Moore’s Law can be leveraged to develop a low SWaP commercial PNT payload for integration into a commercial microsatellite bus with standard interfaces. TrustPoint’s C-band PNT payload is CubeSat compatible and less than 2 kg in mass, providing stable, high-power C-band transmission capability, onboard navigation message generation, and precision GPS-independent timekeeping—all packaged in a form factor that fits in the palm of your hand. Leveraging low-cost, widely-available COTS products integrated in a proprietary electromechanical configuration that is space-qualified for moderate LEO orbits, TrustPoint has designed, integrated, tested and launched the first purpose-built, commercial microsatellites capable of transmitting next-generation C-band LEO PNT signals as both a complement to GPS /GNSS and an independent A-PNT source.

Commoditized Launch. Deployment and sustainment of a proliferated LEO constellation of hundreds of satellites necessitates low-cost, reliable and timely space launch services. Over the last 5 years, commoditized rideshare launch services from multiple commercial launch providers have been introduced into the market and matured, driving orders of magnitude reductions in launch pricing that have made access to LEO affordable for non-government entities. Commercial offerings such as SpaceX’s SmallSat Rideshare Program, with its Transporter and Bandwagon mission series, have provided unprecedented routine access to standard LEO orbits including Sun-Synchronous Orbit (SSO) and mid-inclination, at sub-$5,000 per kilogram pricing (Figure 3). Coupled with orbital transfer vehicles (OTVs) that provide “last-mile” delivery services to specific orbital slots, entire planes of a proliferated LEO constellation can be populated from a single launch opportunity at a fraction of the cost of a single heritage GNSS satellite, which requires a dedicated launch service to a single orbital slot in MEO. 

As additional medium-lift and heavy-lift class launch vehicles emerge and become viable in the commercial space ecosystem within the next 5 years, e.g., SpaceX’s Starship, Rocket Lab’s Neutron, Blue Origin’s New Glenn, and others, the launch cost per kilogram is projected to continue decreasing, enabling affordable LEO constellation deployment and sustainment. System design considerations and optimizations such as standard satellite form factors compatible with industry-standard separation systems, standard LEO orbits at moderate altitudes, and advance bulk buys of launch capacity have the potential to further reduce launch pricing at the scale necessary for proliferated LEO PNT.

Geographic Diversity. From LEO altitudes, a single satellite transmits to less than 10M km2 of effective surface area, whereas a single GNSS satellite at MEO transmits to 200M km² of surface area (Figure 4). At first glance, this 20x increased Field-of-View for GNSS from MEO appears to put LEO PNT systems at a disadvantage—but GPS was optimized for global “one-size-fits-most” PNT, and this approach is no longer effective for increasing numbers of civil, commercial, and military users and applications demanding flexibility and bespoke services in uncertain and evolving environments. The smaller footprint of LEO satellites, coupled with end-to-end software and firmware reprogrammability by design, provides an advantage in that signal parameters can be dynamically varied over different parts of Earth. On the same orbit revolution, a TrustPoint satellite can service the Continental United States with a given signal, then Asian markets with a different signal, and then mainland European markets with yet a different signal. The flexibility of this PNT-as-a-Service business model has nascent dual-use commercial and defense applications, and further is a wartime deterrent in that reconstitution of degraded PNT capability is as rapid as an on-orbit software update, or command uplink to increase the number of satellites tasked with transmitting a desired signal over the impacted area as a countermeasure.

Angular Velocity. According to Keplerian motion, the orbital speed of a circular LEO orbit is about twice as fast as a circular MEO orbit. Range rates between terrestrial users and LEO satellites depend on factors such as the latitude of the user and the altitude and inclination of the satellite, and are on the order of 10 to 15x faster than range ranges that are typical for GNSS satellites (Figure 5, left). The result is single LEO satellite accesses are on the order of 5 to 10 minutes as compared to 3 to 4 hours during which single GNSS satellites are in view from a given terrestrial user in the absence of line-of-sight obstructions. Because the Doppler shift of the carrier frequency is directly proportional to both the range rate and the carrier frequency, it follows that the increase in range rate for LEO orbits, coupled with the increase in frequency from L-band to C-band, leads to Doppler shift that is 30x greater for C-band LEO than the Doppler shift that is typical for L-band GNSS from MEO (Figure 5, right).

Although increased angular velocity makes signal acquisition more challenging, and drives requirements for advanced acquisition techniques and increased data rates to ensure rapid time-to-first-fix (TTFF), increased range rates resulting from faster orbital speeds in LEO have the benefit of rapidly-changing overhead geometries that reduce outages for urban canyon users, and have the potential to accelerate carrier phase ambiguity resolution timelines. Given a LEO satellite has a 10x faster range rate than a MEO satellite, and the L-band wavelength is approximately f_C1/f_L1 = 3.2x longer than the C-band wavelength (6 cm), the resulting rate of change in carrier phase for TrustPoint’s C1 signal is 30x faster than for L-band GNSS from MEO, which has implications for cycle slip detection and integer ambiguity resolution.

Signal and Service Design Considerations

Frequency Diversity. As the RNSS allocation in L-band becomes increasingly congested with current and planned GNSS signals in MEO and LEO, the international GNSS community has begun to consider alternative frequencies for satellite navigation services, specifically unused RNSS allocations at C-band. In addition to L-band congestion driven by future GNSS signals, the criticality of frequency diversity also emerges from global proliferation in GNSS L-band jamming and spoofing threats. Electromagnetic Interference (EMI) at L-band is becoming increasingly prevalent worldwide as low-cost COTS hardware and open-source software enable turnkey GNSS degradation, denial and spoofing capability for bad actors, impacting civil, commercial, military, and even LEO satellite users. The global GPS anti-jamming system market size was estimated at $4.3 billion in 2021 and is expected to grow to $6.1 billion by 2028 as commercial providers of GNSS chips, receivers and augmentation services continue to implement hardware/software solutions for GNSS jamming and spoofing mitigation. However, the prevalent commercial user base of L-band GNSS does not use bespoke anti-jam or anti-spoof equipment due to higher relative cost or SWaP constraints, leaving sectors such as critical infrastructure and commercial aviation susceptible to EMI threats as a result of their continued dependence on low-power, unencrypted heritage signals at L-band, specifically GPS L1 and L2.

To address demand signals for PNT frequency diversity from the civil, commercial and military markets, TrustPoint has filed for global spectrum rights at the ITU for the C-band RNSS/RDSS allocation, and has developed a next-generation A-PNT service and signal set purpose-built for reconfigurability and enabling our vision of PNT built on signals at smaller wavelengths transmitted from smaller orbits (LEO). In future multi-source user equipment built on open architectures and data standards, incorporating C-band A-PNT signals alongside existing L-band GNSS signals, and signals of opportunity from Ku/Ka-band SATCOM systems, offers the potential for significant improvements in PNT service availability and resiliency through diversification of architectures.

Received Signal Power. For equivalent distance, Free Space Path Loss (FSPL) at C-band is a factor of (f_C1/f_L1)² = 10.2x stronger (10 dB) than at GPS L1. The downside of increased FSPL at C-band is that Received Signal Strength (RSS) at the user will be reduced accordingly, unless the loss is compensated for elsewhere in the transmit side of the architecture. For TrustPoint, the 10 dB loss from increasing the carrier frequency from L-band to C-band is compensated for by lowering the space segment to 500 to 700 km LEO altitudes, for which the FSPL at the equivalent carrier frequency is reduced by 31 dB at zenith and 23 dB at 10° elevation angle, assuming a reference LEO altitude of 550 km. Therefore, the net effect of shifting the space segment from L-band MEO to C-band LEO is a +21 dB gain at zenith and +13 dB gain at 10° elevation, when considering the combined effects of carrier frequency, orbital altitude, and FSPL only. This power margin can then be allocated directly into the required minimum RSS at the user, or the prudent system architect could choose to trade this margin to decrease transmit EIRP requirements, and in doing so take advantage of SWaP reductions in the space segment.

A notional comparison of RSS at the input to the user antenna for L-band MEO, C-band MEO and C-band LEO cases is provided in Table 2. To achieve the same -158 dBW RSS as the L-band MEO, the C-band MEO system requires a kilowatt-class transmitter to compensate for the increased free space path loss and tropospheric attenuation at C-band. Transmit hardware of this class carries material technical challenges including larger SWaP, higher development and production costs, and significant thermal management considerations. Conversely, the C-band LEO system achieves -158 dBW RSS with only a 15 W (11.8 dBW) transmitter and 8 dBi gain antenna, both of which are microsatellite-compatible with multiple existing hardware solutions on the market today.

Signal Security. TrustPoint’s C-band A-PNT signal incorporates commercial best practices in cryptographic confidentiality of navigation message data, and time-delayed cryptographic authentication of the same data to mitigate spoofing attacks. This includes the use of the Advanced Encryption Standard [11] and a navigation data authentication method similar to the lower-overhead TESLA method [12]. Encryption keys rotate regularly to protect the integrity of the C-band service and deter unauthorized access. Authentication of navigation message data ensures the data as received by the user is signed by TrustPoint and thus approved for use in forming corrected pseudorange observables supporting Position, Velocity and Time (PVT) solutions. This is a counterpoint to the heritage GPS L1 and L2 signals, which do not inherently offer either confidentiality or authentication protections for users.

Advanced Data Elements. One of the benefits of designing a commercial LEO PNT system and service is the ability to clean-sheet the navigation message structure and enable the opportunities for civil, commercial and military users to embed bespoke data of their choosing within the constraints of the defined message structure. Data rates need not be as high as commercial Ku/Ka-band SATCOM services to provide the dual-use commercial benefits and military utility of embedding GNSS integrity, clock and ephemeris corrections, and/or other augmentation information within the LEO PNT navigation message.

C-Band Attenuation and Propagation Delay Considerations

How do the signal attenuation and propagation delay differ between the C-band LEO GNSS and the L-band MEO GNSS? Table 3 provides a quantitative, side-by-side comparative analysis of RF attenuation and path delay considerations for these two approaches. C-band LEO GNSS benefits from superior FSPL and significantly lower ionospheric effects (attenuation and delay), incurs modestly increased losses due to tropospheric effects, and is more resilient to multipath errors as a result of the combination of shorter wavelengths at C-band and faster geometry changes at LEO.

Next Generation PNT

This article on LEO GNSS at C-band has outlined macroscopic cost and benefit trades for a commercial LEO GNSS system and service in the 5010 to 5030 MHz band, inclusive of space segment architecture, signal and service design, and RF attenuation and propagation delay considerations. Notably, TrustPoint’s vision for next-generation PNT services supporting humanity’s interconnected, autonomous and augmented future is one in which cooperative C-band LEO PNT services are an independent and trusted input into intelligent multi-source PNT fusion engines leveraging commercial PNT signals, heritage GNSS signals, signals of opportunity, and local sensors for resilient PNT that benefits from diversification of architectures and modalities.

The authors of the 2007 Inside GNSS article, “A Role for C-Band?”, leave their readers with the following prospects for a future C-band system:

“Could we not perhaps apply similar ideas to C-band in order to avoid the high power figures that are needed to compensate for the higher propagation losses of the C-band? Another approach might be to design C-band satellites that only serve users in certain locations and then allow satellite transmissions only while flying over those designated regions and for selected periods of time. Such a time-multiplexing could indeed prove to be interesting one day. Equally interesting would be to use special C-band-emitting satellites with LEO orbits to cope with the problem of signal power loss and navigation data transmission.”

Now, 18 years later and in the context of a commercially-driven NewSpace ecosystem, TrustPoint is doing just that—and C-band for LEO PNT isn’t just “interesting”; it is critical for resilient PNT in the face of global proliferation in L-band GNSS jamming and spoofing. 

References 

(1) Hein, G. W., Irsigler, M., Avila-Rodriguez, J. A., Wallner, S., Pany, T., Eissfeller, B., and Hartl, P. (2007). Envisioning a Future GNSS System of Systems Part 3: A Role For C-Band? Inside GNSS, Pages 64–73.

(2) EU Agency for the Space Programme (2024). EUSPA EO and GNSS Market Report 2024. Technical Report, EU Agency for the Space Programme.

(3) Prol, F. S., Ferre, R. M., Saleem, Z., Valisuo, P., Pinell, C., Lohan, E. S., Elsanhoury, M., Elmusrati, M., Islam, S., Celikbilek, K., Selvan, K., Yliaho, J., Rutledge, K., Ojala, A., Ferranti, L., Praks, J., Bhuiyan, M. Z. H., Kaasalainen, S., and Kuusniemi, H. (2022). Position, Navigation, And Timing (PNT) through Low Earth Orbit (LEO) Satellites: A Survey on Current Status, Challenges, and Opportunities. IEEE Access, 10:83971–84002.

(4) Morales Ferre, R., Praks, J., Seco-Granados, G., And Lohan, E. S. (2022). A Feasibility Study for Signal-In-Space Design for LEO-PNT Solutions with Miniaturized Satellites. IEEE Journal on Miniaturization for Air and Space Systems, 3(4):171–183.

(5) More, H., Gerardi, R., Stallo, C., Sanctis, M. D., And Cianca, E. (2022). PNT through Optimised LEO Constellation and INS. In Proceedings of the 35th International Technical Meeting of the Satellite Division of the Institute of Navigation (ION GNSS+ 2022), Pages 1428–1441, Denver, Colorado.

(6) The Business Research Company (2024). Small Satellite Global Market Report 2024. Technical Report, The Business Research Company.

(7) BryceTech (2024). SmallSats by the Numbers 2024. Technical Report, BryceTech.

(8) Erwin, Sandra. “Space Force pauses GPS satellite orders due to excess inventory. Space News. March 13, 2023. spacenews.com/space-force-pauses-gps-satellite-orders-due-to-excess-inventory/

(9) Goeller, L. And Tate, D. (2014). A Technical Review of Software Defined Radios: Vision, Reality, and Current Status. In 2014 IEEE Military Communications Conference, Pages 1466–1470.

(10) 360 Research Reports (2024). Global GPS Anti-Jamming System Market Report. Technical Report, 360 Research Reports.

(11) National Institute of Standards and Technology (2001). Advanced Encryption Standard (AES). Technical Report FIPS 197, U.S. Department of Commerce, Gaithersburg, MD, Updated May 9, 2023.

(12) Anderson, J., Lo, S., And Walter, T. (2022). Cryptographic Ranging Authentication with TESLA, Rapid Re-Keying, and a PRF. In Proceedings of the 2022 International Technical Meeting of the Institute of Navigation, Pages 43–55, Long Beach, California.

(13) Misra, P. And Enge, P. (2012). Global Positioning System: Signals, Measurements, And Performance. Ganga-Jamuna Press, 2 Edition.

(14) Hunsucker, R. D. and Hargreaves, J. K. (2003). The High-Latitude Ionosphere and its Effects on Radio Propagation. Cambridge University Press.

(15) Béniguel, Y. (2002). Global Ionospheric Propagation Model (GIM): A Propagation Model for Scintillations of Transmitted Signals. Radio Science.

(16) ITU-R (2022). Attenuation by Atmospheric Gases and Related Effects (Recommendation P.676-13).

(17) ITU-R (2017). Propagation Data and Prediction Methods Required for the Design of Earth-Space Telecommunication Systems (Recommendation P.618-13).

(18) ITU-R (2005). Specific Attenuation Model for Rain for Use in Prediction Methods (Recommendation P.838-3).

(19) ITU-R (2019). Attenuation due to Clouds and Fog (Recommendation P.840-9).

(20) ITU-R (2016). Attenuation in Vegetation. (Recommendation P.833-9).

(21) De Bast, S., Sleewaegen, J.-M., and De Wilde, W. (2023). Analysis of Multipath Code-Range Errors in Future LEO-PNT Systems. Engineering Proceedings, 54(1).

Authors

Dr. Paul Anderson is Lead Systems Engineer for TrustPoint, where he leads the development and deployment of proliferated space and ground segments enabling TrustPoint’s commercial C-band PNT services. He brings more than 12 years of experience in astrodynamics, state estimation, space systems engineering, and IV&V across the program lifecycle. He joined TrustPoint from VOX Space, subsidiary of Virgin Orbit, where he led systems engineering for microsatellite launch integration and responsive mission execution. Prior to VOX Space, he led technical teams at The Aerospace Corporation in support of the GPS space and ground segments, multi-source PNT, and RF geolocation. He brings a mission-driven, technically oriented, people-focused approach in pursuit of 100% mission success at scale. He holds a Ph.D. in Aerospace Engineering Sciences from the University of Colorado Boulder.

George Schmitt is Signals and Processing Lead for TrustPoint, where he drives the company’s waveform design, RTL development, and advanced signal processing efforts, bringing more than 30 years of expertise in digital signal processing, secure communications, and RF system design. His career includes senior technical roles at The Aerospace Corporation, where he developed resilient satellite and ground communication systems for the DOD and intelligence community, and technical leadership positions at Naval Research Laboratory and Orbital Sciences, where he led rapid prototyping on FPGA and GPU platforms. Known for his deeply analytical and hands-on approach, his technical skills span VHDL, Verilog, MATLAB, encryption, radar, comm, and PNT waveform design, and high-speed data protocols. He holds a B.S. in Mathematics and Computer Science from the Massachusetts Institute of Technology.

Dr. Furqan Ahmed is a Senior GNSS Scientist at TrustPoint, where he focuses on the development of PVT engines, channel modeling for LEO PNT signals, and simulation of GNSS observations for TrustPoint’s commercial C-band PNT services. He also contributes to payload software development for TrustPoint’s LEO satellites. Previously, he worked in the GNSS positioning engine teams at Qualcomm and Garmin. Prior to joining the PNT industry, he spent time in academia where his research focused on geodetic and atmospheric applications of GNSS. He holds a Ph.D. in Engineering Sciences from the University of Luxembourg.

Patrick Shannon is CEO and co-founder of TrustPoint. Prior to co-founding TrustPoint, he was the VP of Business Development and Operations at Astro Digital where he was responsible for strategy formulation, business development, and product management. During his tenure at Astro Digital, he directly led five satellite programs and a 400% increase in revenue over a three-year period. Before that, he was VP of Business Development at SpaceQuest, where he drove company strategy and oversaw all contract and internal R&D program execution. He got his start as a satellite systems engineer at Orbital Sciences, later transferring to the Corporate Strategy group supporting M&A and government relations. He holds a BS in Aerospace Engineering from MIT and a MS in Management Science and Engineering from Stanford University.

The post The Case for LEO GNSS at C-Band appeared first on Inside GNSS - Global Navigation Satellite Systems Engineering, Policy, and Design.

ZIXI LIU, SHERMAN LO, TODD WALTER AND SAM PULLEN, STANFORD UNIVERSITY

These events come in many different forms and can cause signal loss (“jamming”) and deliberate errors (“spoofing”), making their impacts difficult to assess and categorize. While RFI from unintentional emitters (e.g., RF transmitters for other applications such as television and radar) continues to occur as it has historically, the dominant threats to GNSS navigation now appear to come from deliberate denial or warping of service by military combatants. This RFI is generally not targeted at civil users but is nevertheless causing significant and unexpected GNSS degradations [1].

This article is a follow-up to the March/April 2024 GNSS Solutions column [2]. It describes an updated, comprehensive methodology for RFI detection and localization and shows recent results from it [3]. It also introduces an online tool developed by Stanford University (rfi.stanford.edu) that automatically collects publicly available Automatic Dependent Surveillance (ADS)-B messages and generates estimates of GNSS RFI locations and impacts [4].

Using ADS-B Messages and NIC Values 

As explained in [2], our research uses ADS-B observations that contain GNSS-derived aircraft position information along with corresponding signal quality metrics and are updated every 0.4 to 0.6 seconds at the 1090 MHz frequency. ADS-B data provides good coverage of high-altitude aircraft and allows us to create a “crowdsourced” sensor network by collecting information from multiple aircraft simultaneously. ADS-B data is available from several public sources such as the OpenSky Network [5] and ADS-B Exchange [6], and it is used by GPSJam [7] and the Zurich University of Applied Sciences (ZHAW)and SKAI Data Services [8] to show locations and times of apparent RFI. 

As explained in [2], GNSS RFI analysis using ADS-B relies upon the values for Navigation Integrity Category (NIC) defined by the RTCA ADS-B MOPS (DO-260C) [9] that estimate the transmitting aircraft’s GNSS position quality. NIC gives the 2D horizontal error radius (or “containment radius”) that should bound the actual horizontal position error with a probability of 0.99999 (i.e., the probability of unknowingly violating this bound is 10^-5or lower). Figure 1 (repeated from [2] for convenience) shows the NIC values that can be transmitted and their corresponding containment radii. Higher NIC integer values correspond to smaller error bounds and thus better performance.

NIC values are used to distinguish between aircraft with apparently nominal GNSS measurements and those that are degraded due to (most likely) RFI. A NIC of 7 corresponds to a horizontal containment radius of 370.4 meters. This is taken to be the smallest NIC value (largest containment radius) that corresponds to nominal behavior (typically, nominal NIC values are 8 or higher). Any NIC below this (especially NIC=0) is treated as representative of RFI.

Example Spoofing Events

Figure 2 shows three examples of spoofing from ADS-B observations on August 15, 2024 (left and middle plots) and November 25, 2023 (right plot) [3]. In the first example (left plot), multiple aircraft were spoofed into a static position at Beirut-Rafic Hariri International Airport in Lebanon. The second event (middle plot), over Smolensk Oblast, Russia, spoofed aircraft into circular flight paths. In the third example (right plot), spoofed aircraft were diverted into false landing trajectories over the runway at Belbek Airport near Sevastopol, Crimea. These cases demonstrate that spoofed positions can remain static or change dynamically. Powerful jamming and spoofing events continue to occur, underscoring the importance of quickly detecting and localizing such events.

ADS-B-Based Spoofing Analysis Methodology

Stanford has developed a multi-step spoofing detection and localization approach that is described in detail in [3]. The steps of this method are summarized as follows: 

1. Position jump detection: The detection algorithm searches for position jumps for each aircraft in the ADS-B database using a Kalman filter (KF) to reduce errors in the reported aircraft positions. The Kalman filter estimates aircraft velocity from position data. If the estimated velocity for a particular aircraft exceeds 650 m/s (approximately Mach 2 at an altitude of 12,000 ft or 3,660 m), the corresponding aircraft locations are flagged as potentially spoofed.

Figure 3 presents a flight on November 25, 2023, with a position jump detected by this method. The left side displays the aircraft’s flight trajectory color-coded by the NIC values reported by ADS-B. The yellow diamond indicates the starting point prior to the jump, while the pink square represents the endpoint after the jump. This flight was spoofed from its original trajectory near Bucharest to Belbek Airport, resulting in a sudden trajectory jump that suggested an unrealistic and non-physical velocity exceeding Mach 2 because the aircraft was spoofed into that path rather than actually flying it.

2. Analysis of flagged locations: Potentially spoofed points detected across all aircraft are clustered temporally using the Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm [10]. Figure 4 shows how DBSCAN is used for this. The logic behind DBSCAN is shown in the left-hand graphic and involves setting a minimum number of points (m_min) and a maximum allowable distance (ε) between points within each cluster. Points are considered “density-reachable” from one another (and thus form a group) based on these criteria. Unlike other clustering algorithms, DBSCAN does not require pre-specification of the number of clusters. This is important because the number of RFI events occurring at any given time is unknown. On the right, an example group from the worldwide clustering results identifies the Belbek Airport spoofing event. The trajectories are color-coded by aircraft to illustrate how multiple aircraft were spoofed into false paths on the runway at Belbek Airport during this event.

3. Interpolation within spoofed regions: Once an apparent spoofing event is detected, the identified spoofed points are used to attempt to locate it. First, specific spoofed points are identified, allowing us to determine the last observed position before spoofing and the first observed position after recovery from spoofing. These mark the start and end of the spoofed segment. To reconstruct the flight path, we first remove spoofed points from the trajectory. We then interpolate the complete flight path using locations from the non-spoofed points. Each spoofed point is then mapped to its corresponding interpolated position based on its timestamp. An example of this is shown in the upper two plots in Figure 5 that show where one aircraft was actually flying on November 25, 2023, while being spoofed. Applying this method to all affected aircraft provides an estimate of the region affected by spoofing and its spatial extent, as depicted in the lower two plots of Figure 5. 

4. Line-of-Sight Localization Analysis: The second phase of localization involves line-of-sight analysis. Any spoofer within the line of sight of a potentially spoofed point can influence that point. This avoids requiring any assumptions regarding the type of antenna used by the spoofer. A 2D grid of ground locations is constructed to represent all possible spoofer transmitter locations. For each spoofed point, a circle is drawn with a radius equal to the radar horizon range. The spoofer must be located within or on the boundary of these circles to impact the corresponding spoofed locations.

The region with the greatest overlap among the circles is identified as the most likely spoofer location with the constraint that the spoofer’s location should not be in an area that would also affect non-spoofed points. For each spoofed point, only those non-spoofed points that are observed within the same millisecond are included in this constraint. This approach helps prevent errors that may arise when spoofer transmissions are intermittent (see [3] for details).

Results for December 25, 2023

The method described above supports daily worldwide detection and localization of spoofing events observed in ADS-B transmissions. Figure 6 presents example detection results for December 25, 2023, portions of which were previously documented in [2]. Figure 7 shows the corresponding region affected by those spoofing events. On that day, five significant spoofing events were observed. The first event affected aircraft that were flying across the southwest portion of the Black Sea and spoofed them into fake landing trajectories at Belbek Airport near Sevastopol, Crimea. The second event contains multiple affected regions crossing the borders of Latvia, Lithuania, Belarus and Russia in which aircraft were spoofed into circular trajectories near Smolensk. The other three were instances of static spoofing into fixed positions. The first event spoofed flights near the coastline of Lebanon into static positions at Beirut Airport. The second event spoofed flights along Baghdad and Kuwait to static locations near Najaf, Iraq. The third event spoofed flights passing through the center of Iraq to static locations near Samarra, Iraq and Baghdad [3]. 

Worldwide Visualization

Our lab recently activated a website (rfi.stanford.edu) that uses these methods to translate ADS-B observations into visualizations of where RFI is occurring and how severe and widespread it is. Figure 8 shows a screenshot of the home page of this site with the (adjustable) date set to October 23, 2024. This page shows a “heat map” of RFI locations east of 125ºW longitude and west of 70ºE longitude (although the entire world is shown online) based on the percentage of aircraft in each map cell with low NIC (< 7). Most areas of the world are green because no aircraft with low NIC values were observed. Red regions are those with more than 10% of aircraft with low NIC and strongly suggest the presence of RFI during at least part of the day. The parts of the map shown in white either have low levels of air traffic or are difficult to obtain ADS-B measurements from. The online map supports zooming in to more precisely see where significant RFI is occurring.

Each location with a blue pointer in Figure 8 represents a detected RFI event. Clicking on any of these events presents a more detailed map of the aircraft and region affected. Figure 9 shows the map of the event near Muscat, Oman, on this day. It identifies actual aircraft paths with low NIC (in red) that appear to be affected by RFI along with aircraft paths with high NIC (mostly in gray, representing NIC=8). There is some overlap between low and high NIC points, but an approximate identification of the locations affected by RFI effects can be made. A movie showing aircraft movement around this region over the entire day is also presented on this page to help refine this estimate in both space and time.

The website includes observations stretching back to the beginning of 2024 and will automatically collect new results going forward. Thus, it supports comparisons of RFI locations and impacts over time. Figure 10 shows aircraft affected by the same RFI event detected near Muscat, Oman on January 23, 2024 (nine months earlier than the results in Figure 9). The regions affected in Figure 10 are similar to those in Figure 9, suggesting the same interference source. This event is also present (with minor variations) on the 23rd day of several other months randomly checked between January and October.

Clicking the “Dashboard” link on the upper left side of the screenshot in Figure 8 brings up a series of plots for the month selected (in this case, October 2024 up to October 24). Figure 11 shows one of these plots with the overall number of detected RFI events on each day. This number varies between 60 and 80, suggesting the degree and extent of RFI remained relatively constant over the month. 

The website is continually updated and will soon incorporate additional information focused on detected and located spoofing events. 

Summary 

While RFI jamming and spoofing events have become troublesome for civil users and are likely to continue to increase, more information than ever is available to help identify their location, extent, frequency and severity. Position and NIC information in recorded ADS-B transmissions makes it possible to evaluate RFI locations and impacts over most of the populated world and to better understand them. The methodology described here makes use of this wealth of data to detect and locate RFI events in an automated fashion so that the results can be accessed and investigated online.

This analysis supplements the recently released report on GPS spoofing observations and aviation impacts provided by the GPS Spoofing Workgroup 2024 [1]. One of the key findings in [1] is, “The Workgroup noted many misconceptions about the reason GPS Spoofing is occurring. With few exceptions, GPS Spoofing is conducted by state actors as a result of regional conflict. The Workgroup found no examples of a direct, targeted attack on a civilian aircraft.” 

Acknowledgments

The authors would like to thank the FAA for its support of this research as well as the other members of our laboratory and Prof. Dennis Akos of the University of Colorado for their contributions to this research. We also thank the ADS-B data sources used in our analyses and at rfi.stanford.edu: the OpenSky Network [5] and the ADS-B Exchange [6].

References

(1) GPS Spoofing: Final Report of the GPS Spoofing Workgroup, OPSGROUP, Sept. 2024. https://ops.group/blog/gps-spoofing-final-report/

(2) Z. Liu, S. Lo, et al., “GNSS Solutions” column, Inside GNSS, Vol. 19, No. 2, March/April 2024, pp. 28-35. https://lsc-pagepro.mydigitalpublication.com/publication/?m=61061&i=818266&p=28&ver=html5

(3) Z. Liu, S. Lo, et al., “GNSS Spoofing Detection and Localization Using ADS-B Data,” Proceedings of ION GNSS+ 2024, Baltimore, MD, Sept. 2024 (forthcoming).

(4) “GNSS Interference Detection Using ADS-B (website)” GPS Laboratory, Stanford University, https://rfi.stanford.edu or https://waas-nas.stanford.edu

(5) “The OpenSky Network—Free ADS-B and Mode S data for Research,” https://opensky-network.org/

(6) “ADS-B Exchange: World’s largest source of unfiltered flight data,” https://www.adsbexchange.com/

(7) J. Wiseman, “GPSJam: Daily Maps of GPS Interference,” https://gpsjam.org/

(8) “Live GPS Spoofing and Jamming Tracker Map,” https://spoofing.skai-data-services.com/

(9) Minimum Operational Performance Standards for 1090 MHz Extended Squitter Automatic Dependent Surveillance—Broadcast (ADS-B) and Traffic Information Services—Broadcast (TIS-B). Washington, DC, RTCA DO-260C, Dec. 17, 2020.

(10) M. Ester, H.-P. Kriegel, et al., “A density-based algorithm for discovering clusters in large spatial databases with noise,” Proc. of AIAA KDD-96, pp. 226–231 (1996).

Authors

Zixi Liu is a Ph.D. candidate at the GPS Laboratory at Stanford University. She received her B.Sc. degree from Purdue University in 2018 and her M. Sc. degree from Stanford University in 2020.

Sherman Lo is a senior research engineer at the Stanford GPS Laboratory and the executive director of the Stanford Center for Position Navigation and Time. He received his Ph.D. in Aeronautics and Astronautics from Stanford University in 2002. He has and continues to work on navigation robustness and safety, often supporting the FAA. He has conducted research on Loran, alternative navigation, SBAS, ARAIM, GNSS for railways and automobiles. He also works on spoof and interference mitigation for navigation. He has published over 100 research papers and articles. He was awarded the ION Early Achievement Award.

Todd Walter is a Research Professor in the Department of Aeronautics and Astronautics at Stanford University. He is also a member of the National Space-Based Positioning, Navigation, and Timing (PNT) Advisory Board. His research focuses on implementing satellite navigation systems for safety-of-life applications. He has received the Institute of Navigation (ION) Thurlow and Kepler awards. He is also a fellow of ION and has served as its president.

The post Q: What has been learned recently about GNSS RF jamming and spoofing events? What tools are available online to track and investigate these events? appeared first on Inside GNSS - Global Navigation Satellite Systems Engineering, Policy, and Design.

The result is an enhanced infrastructure that drives Galileo toward full operational capability while securing Europe’s position as a leader in satellite navigation.

With 32 satellites orbiting Earth after the system’s thirteenth successful launch, Galileo, which has been operational since 2016, delivers meter-level accuracy to users worldwide. At the core of this system is the Galileo Ground Segment, developed and maintained by a collaboration of top European aerospace entities: the European Space Agency (ESA), Thales Alenia Space, Spaceopal (DLR GfR and Telespazio), the European Commission (EC) and the European Union Agency for the Space Programme (EUSPA).

The Galileo Ground Segment is a vast and intricate system comprising:

• Two Galileo Control Centres (GCC) located in Italy (GCC-I) and Germany (GCC-D), ensuring redundancy.

• Two Galileo Security Monitoring Centres (GSMC) based in Spain (GSMC-E) and France (GSMC-F).

• A global network of uplink (ULS) and sensor stations (GSS).

• The Galileo Data Dissemination Network (GDDN), a dedicated network, controlled and managed end-to-end by the Galileo program (no dependency on the internet) and which gives continuous availability.

• Seven External Entities (EE), including the Galileo Service Centre (GSC) for service monitoring and the Return Link Service Provider (RLSP), which supports Galileo’s Search and Rescue (SAR) service, connected via the External Data Distribution Network (EDDN).

On March 11 at 13:39 UTC, Galileo satellites started transmitting the first navigation message from the newly upgraded Ground Segment System Build 2.0 (SB 2.0). This landmark event heralded several critical improvements that not only enhanced current operations but also laid the groundwork for future Galileo architectures, such as the upcoming Galileo Second Generation’s.

Key features of the SB 2.0 upgrade include:

• Modernized Ground Mission Segment (GMS) infrastructure with enhanced resilience.

• Enhanced Public Regulated Service (PRS).

• Strengthened security monitoring via the Security Operations Centre at the Galileo Security Monitoring Centres.

• Upgraded cybersecurity protections.

• Preparations for future developments, including the transition to Galileo Second Generation.

The migration of the Ground Segment to SB 2.0 was achieved without disruption to Galileo’s vast user base, thanks to meticulous planning based on lessons learned from previous upgrades, particularly the Ground Mission Segment update in 2019. This article dives deeper into the specifics of how this intricate and challenging upgrade was accomplished.

Ensuring Seamless Operation: The Upgrade Strategy

A system relied upon by four billion users every day cannot afford any significant downtime. To avoid this, the upgrade strategy for Galileo’s Ground Segment was carefully crafted and executed through six distinct phases.

Phase 1: Upgrade approach and design

The initial step in upgrading the GMS infrastructure involved designing an effective and robust migration strategy while adhering to key constraints outlined by Galileo stakeholders:

• Maintain business continuity throughout the migration process.

• Avoid introducing any single points of failure.

• Validate all intermediate system configurations.

• Rehearse all upgrade steps.

• Ensure rollback capability at every stage of the upgrade.

To meet these stringent requirements, the concept of a pre-operational (pre-OPE) chain was introduced as the upgrade solution. The pre-OPE chain is a fully redundant and upgraded GMS Core infrastructure, incorporating both GCCs and GSMCs, updated to ground segment version 3 (V3). Meanwhile, the existing operational (OPE) chain, based on version 2 (V2), remained isolated. This approach offered several advantages over previous migration strategies:

• Continuous chain redundancy throughout the deployment and upgrade.

• Simplified upgrade steps.

• Shortened overall upgrade duration.

• Flexible scheduling of upgrade activities without inter-chain constraints.

• Easier and more efficient rollback procedures.

During this phase, the migration team developed a comprehensive plan, covering design adjustments, validation methods, and the steps for migration and accreditation.

Phase 2: Deployment and validation of pre-operational chain

In the nominal setup, each Galileo Center is equipped with:

• An OPE chain managing operations to the spacecrafts and delivering real-time service to the users via the network of worldwide antennas.

• A validation (VAL) chain used for validation of new features, troubleshooting and operator training purposes. The VAL chain is not connected to any of the antennas worldwide, however, it gets the observables forwarded from the OPE chain.

A dedicated pre-OPE space was established in the two GCCs and the two GSMCs. More than 90 components were either newly deployed or upgraded during this phase, involving more than 400 individual installations, a process that spanned 2.5 years. On the other hand, two of the four VAL chains were updated to V3 in GCC-D and GSMC-E.

After completing the deployment of the pre-OPE chain to each site, the pre-OPE chains were interconnected, but always fully segregated from the OPE chains, to not interfere with the service provision. Further, as for the VAL chain, the pre-OPE chains got all the data from the antennas worldwide without being connected to them.

This parallel deployment allowed both OPE and pre-OPE systems to operate side by side to:

• Train operational personnel on new functions brought by ground segment V3 as well as verifying team readiness on routine operations.

• Verify pre-OPE robustness in the targeted real-time operational environment. 

• Demonstrate that pre-OPE delivers a navigation message performance in line with the demanding requirements in terms of orbitography and clock synchronization.

In such a complex system of sub-systems, an extensive configuration and tuning effort of several weeks was unavoidable to determine and baseline the final working point of the chain. A final validation campaign allowed to state the readiness of the pre-OPE, demonstrating it is ready to deliver service.

Phase 3: Rehearsal of the migration

Phase 3 focused on rehearsing the migration with the objective to establish and validate the operational procedures achieving a seamless service transition from V2 to V3 and demonstrating rollback capabilities that can be triggered at any point during the migration execution to guarantee the service alive. These operational procedures contain actions such as disconnecting or connecting cables, moving critical equipment and aligning operational context between OPE and pre-OPE. 

The rehearsal phase spanned seven months, by testing first isolated sequences and then putting together all the pieces of the puzzle to achieve the overall migration sequence. 

To avoid jeopardizing the service provisioning from the OPE chain, it was not possible to test the transition from the V2 OPE chain to the V3 pre-OPE chain during the rehearsal. Consequently, this transition was rehearsed by connecting the VAL chain (still in V2) to the pre-OPE chain, simulating the transition from V2 to V3. 

The original plan was to execute migration for the four control centers in one day. However, the rehearsal phase revealed this approach carried significant risk on the service provision, as many critical activities would need to be performed successfully in a truly brief time, leaving little margin for troubleshooting if issues arose.

During these early runs, unpredictable technical issues surfaced, making it clear the plan to migrate all four chains in one day was too optimistic. The compressed timeline offered little flexibility to address unexpected problems. Consequently, if troubleshooting could not resolve an issue quickly, the entire migration would need to be rolled back, and the process would have to start again from the beginning.

Change of Strategy

After evaluating the challenges faced during the first rehearsal runs, the migration strategy was optimized. Instead of migrating all four chains simultaneously, the team designed a phased approach. First, one GCC V3 would be integrated into the new system. Once the integration was completed, the service would be transferred from one GCC V2 operational chain to the new integrated GCC V3 chain.

After the successful migration of one GCC, the second GCC would undergo the same pre-integration, and only then would a nominal handover be conducted to complete the migration for both GCCs. Following the migration of the two GCCs, the two GSMCs would be migrated.

This new phased strategy significantly reduced the risks associated with the transition and allowed the team to better manage potential issues that might arise during the process.

Final Rehearsal Runs proved the feasibility and effectiveness of the final operational procedures and team readiness, demonstrating the Galileo system could transit smoothly from V2 to V3 without Open Service disruption.

A multitude of technical details was sorted out and several degraded cases could be addressed to push the system to its limits.

Finally, the only missing piece of the puzzle was to ensure the remote sites (i.e. ULS and GSS) could be successfully integrated in the new V3 pre-OPE chain. As explained earlier, the remote sites are only nominally connected to the OPE chain, and the data is then forwarded to the VAL/pre-OPE chain so the VAL or pre-OPE chain does not accidently interfere with the OPE chain’s service provision. After careful planning, one antenna was disconnected from the OPE chain and connected to the pre-OPE chain before the actual migration, verifying the proper integration, i.e. commandability and monitoring capabilities of this antenna from the pre-OPE chain.

After the successful integration of this antenna on the pre-OPE chain, the antenna was re-integrated on the V2 OPE chain. With this, the migration team was confident and enthusiastic to enter the next phase.

Phase 4: Migration of the GCCs

The migration process began on March 4, with the integration of the GCC Germany V3 chain into the operational environment. This involved disconnecting all the remote sites and external entities connected to the Galileo network from the V2 chain in Germany and reconnecting them to the V3 chain, while Italy’s V2 chain continued to provide service.

Throughout the week, more than 50 remote elements were systematically integrated into the GMS V3 at GCC Germany, ensuring each component was properly connected and fully functional. A final alignment of operational contexts between OPE and pre-OPE was executed, ensuring perfectly mirrored chains. The planning context, which included the allocation of ULS antenna contacts to satellites, was one of the alignment items, ensuring a seamless transition from OPE to pre-OPE for the ULS antenna.

During the weekend, after this initial integration, the team continued to carefully monitor the stability of the system and perform routine operations.

On Monday, March 11, the critical service transfer from the GCC Italy V2 chain to the GCC Germany V3 chain took place. The operation commenced at 07:00 CET with more than 200 personnel stationed across all Galileo sites and external entities. Several key actions were undertaken, starting with the 
handover of commanding of all ULS and GSS antennas, one by one, from GCC Italy V2 to GCC Germany V3. During that step, real-time mission data was still disseminated from GCC Italy V2.

Subsequent checks of synchronization took place to confirm time references of both OPE and pre-OPE were aligned to within a tenth of a nanosecond. Such a synchronization is critical, as it guarantees the change of the navigation message from OPE and pre-OPE will have a negligible impact for users.

At 13:39 UTC, real-time mission data dissemination was activated. The first Galileo navigation message was uplinked from the new GMS V3, marking a pivotal moment in the migration process. Throughout the day, teams continued fine-tuning the system and in parallel still operated the legacy GMS V2 version to maintain rollback capabilities in case a critical issue would have occurred on GMS V3. At the end of the day, the GMS V3 chain was operating smoothly, with all Galileo services (OS, HAS, OSNMA, SAR return-link) working nominally. It was an intense, exhausting, but remarkable day for the teams. The pressure was immense, but the months of rehearsals and the strength of the plan proved their worth.

As seen in Figures 7, 8 and 9, Galileo system performance remained excellent and neither a change in the Signal In Space Ranging Error (SISRE) nor a jump on the Galileo System Time (GST) was observed when switching from GMS V2 to V3.

The following day, March 12, the GCS was successfully integrated with the GMS V3. The migration campaign was strategically planned so the critical migration activities would occur on Monday and Tuesday, leaving ample time to address non-critical issues by the week’s end. The entire system was closely monitored until the end of the week and over the weekend to ensure stability.

In the subsequent week, beginning on Monday, March 18, a similar process was conducted at the GCC Italy site. As in Germany, all remote sites and external entities connected to the Galileo network were disconnected from the V2 chain in Italy and connected to the V3 chain, while the Germany V3 chain continued providing service.

The migration of the GCCs concluded with a smooth handover of operations from GCC Germany back to GCC Italy, completing the transition. Throughout the migration, there was no disruption to Open Service users, and the Galileo signal’s stability remained exceptional.

Phase 5: Migration of the GSMCs

Following a period of system stabilization, attention turned to the GSMCs. The migration scenario was strategically designed so the GMS upgrade was executed first, followed by the GSMC upgrade. This approach ensured the overall system could be migrated in a controlled and coordinated manner while still offering rollback capabilities in case of any issues. At the start of Phase 5, the legacy GSMC version remained connected to the new GMS. During this phase, the GSMC was upgraded to version V3.

Phase 6: Upgrade of the worldwide uplink and sensor stations

With the critical upgrades to the GCCs and GSMCs completed, the final phase involved upgrading the worldwide network of uplink and sensor stations.

In May, starting with the GSS in Redu, Belgium, a site quick and easy to access, was chosen to demonstrate the feasibility and allow—if needed—for easy troubleshooting and potential re-visit of the site.

After the successful upgrade of the Redu station, the next upgrade took place on the remote island of La Réunion, a combined Galileo site that supports GSS, ULS and Telemetry and Tracking Stations (TTC). Over six weeks, more than 20 personnel were stationed on site, with additional support from the GCCs and GSMCs in Europe. The sheer complexity of this operation was amplified by the remote nature of Réunion itself, which lies more than 9,000 kilometers away from the ESA’s headquarters in Europe. One of the most significant challenges in Réunion was ensuring all involved parties were synchronized in their efforts. This upgrade required the temporary removal of critical operational assets from service, necessitating tight coordination to prevent any disruptions to Galileo’s global operations.

With Réunion fully upgraded, the focus shifted to the Jan Mayen site in the Arctic Ocean, which was completed in August and will be followed by the other remaining remote sites.

Conclusion

The completion of the SB 2.0 migration represents a remarkable achievement for Europe’s Galileo navigation system. Culminating years of preparation, the upgrade was executed seamlessly over a six-week period, involving more than 200 personnel spread across Europe. This success not only bolsters Europe’s capabilities in satellite navigation but also supports key policy objectives in security, defence, resilience, and global competitiveness.

The new Galileo Ground Segment is now more robust, secure and prepared for the future, ensuring the system continues to provide precision and reliability to its billions of users worldwide. 

Acknowledgements

The successful migration to SB 2.0 marks a significant milestone made possible by the dedication, talent and collaboration of an exceptional team. This achievement reflects the commitment and hard work of each individual involved, and the authors would like to extend their sincere gratitude to all contributors.

We would especially like to thank the European Commission (EC), the EU Agency for the Space Programme (EUSPA), the Security Accreditation Board (SAB) with the support of Member States and the Security Accreditation Department (SADEP), Spaceopal—the main contractor for operational services—as well as all other experts within the European Space Agency and Thales Alenia Space. Your dedication has not only transformed what is possible but will also have a lasting impact on the future of Galileo. Thank you for your outstanding contributions in bringing SB 2.0 to life.

Authors

Miguel Manteiga Bautista is the Galileo program manager, inside the Directorate of Navigation of the European Space Agency. He obtained his MSc degree in 1999 in telecommunications engineering from the University of Valencia, Spain. In 2005, he obtained an International Executive Master in Business Administration from the IE Business School.

After spending his early career developing and deploying high-speed telecommunication networks in Telefonica SA, he moved to the ESA Galileo Team in 2001. Throughout the last 23 years, he has developed his career in the Galileo program in various positions covering all areas of the Galileo environment (space, ground, user, launcher, system, security, operations, project and program management).

In 2015, he took over the position of head of GNSS/Galileo Evolution program, he became Galileo Second Generation Project Manager in July 2020 and has been head of Galileo Programme Office since 2024. He is responsible for the overall program-level implementation of Galileo activities at ESA, in close coordination with the European Commission and European GNSS Agency representatives.

Sonia Toribio holds a master’s degree in computer science from the Universidad Politecnica in Madrid (1999), a master’s degree in system engineering from the Ecole Nationale Supérieure des Télécommunications in Paris (2001) and a master’s degree in Space Systems and Business Engineering from the Delft University of Technology (2011). She has worked on the Galileo Ground Segment over the last 23 years, first in industry and then as part of the Galileo team at ESA.

She has been involved in several areas within the Ground Segment procurement, starting with studies during Phase B back in 2003, then being responsible for the procurement of the Ground Control Segment (GCS) of the Giove A and Giove B satellites (Galileo In Orbit Demonstrators) as well as the In Orbit Validation (IOV) and Full Operational Capability (FOC) Phases.

In 2013, Toribio was appointed as ESA Galileo Ground Control Segment (GCS) Project Manager. In 2020, Sonia was appointed as ESA Galileo Ground Mission Segment (GMS) and Ground Segment Security Project Manager, responsible for the procurement, qualification and delivery of the System Build 2.0 (Public Regulated Service Initial Operational Capability) and the upgrade of the most complex Ground Segment ever built in Europe, which was completed in April 2024.

In 2024, she was appointed as ESA Galileo Ground Segment manager responsible for evolutions of the GCS, GMS and Ground Segment security infrastructure.

Sven Richter holds a master’s degree in computer science from the University of the Federal Armed Forces in Munich, which he completed in 2002. He commenced his professional journey by contributing to the development of safety-critical real-time systems for both the German Military and NATO.

Transitioning to the space industry, he joined the European Space Agency (ESA) in 2010, where he served as an engineer specializing in on-board software for the Solar Orbiter and Sentinel 2 project. In 2016, Richter joined the Galileo project at ESA. Here, he specialized in deployment, integration and verification. He has overseen the Galileo Ground Mission Segment’s deployment activities since 2022.

Anas Tajdine holds a Ph.D. in applied mathematics from the Universidad Complutense of Madrid. He has been involved in European navigation programs development over the last 23 years. He joined Thales Alenia Space in 2013. He has been GMS Performance Manager, Design and Development Manager and WP2x technical manager. He is currently GNSS ground chief engineer for Thales Alenia Space, acting as program design authority and ensuring segment technical coordination.

Vincent Borrel holds a master’s degree in communications engineering from IMT Atlantique engineering school in Brest, which he completed in 2004. He first worked in DLR in Munich in satellite communications studies. He has been involved in the Galileo program since 2005 for Thales Alenia Space, first working on Galileo ground segment algorithms. He then was seconded in ESTEC in 2014 and 2015 on end-to-end system validation, where he was actively involved in the early phases of the Galileo system integration activities, such as first position fix validation. He was then responsible for Galileo PRS service exploitation for Thales Alenia Space and is now technical manager of Galileo Ground Segment migration.

The post Working Papers: Upgrading Galileo appeared first on Inside GNSS - Global Navigation Satellite Systems Engineering, Policy, and Design.

SERGEY ZOTOV EMCORE CORPORATION

With the burgeoning advancements in inertial navigation, the diversity in inertial sensors and their performance grades has expanded. While a comprehensive framework of standards terminology exists, encompassing both military and civilian guidelines (e.g., the IEEE Standard for Inertial Sensor Terminology), their adoption and application remain inconsistent across the industry. This inconsistency poses two principal challenges:

1. Heterogeneity in data representation: When comparing data sheets from different manufacturers, one can easily observe glaring disparities in representation and format. This heterogeneity impedes efficient comparison, making selection processes for end users cumbersome and potentially misleading. 

2. Testing protocol discrepancies: Even with clear guidelines, manufacturers and end users often differ in their understanding and application. This leads end users to independently validate inertial sensors due to inconsistent interpretations of the standards terminology and testing methods. 

Moreover, the industry has recently borne witness to a concerning trend: a misunderstanding, misinterpretation, or even outright neglect of fundamental terms for grades such as tactical, high-end tactical, navigation, and strategic. 

Given these persistent tendence, it is evident that while existing standards serve a fundamental role, there is a need for a more robust and universally adopted top-level terminology standard that clearly documents what is tactical/navigation/strategic grade for INS/IMU and inertial sensors. This standard should not have double interpretation. 

It Should Be Called the Same as it Reckons 

The core function of inertial systems, encompassing inertial measurement units (IMU) and inertial navigation systems (INS), is to provide a standalone solution to the navigation problem. This involves calculating the current position (velocity) and attitude of a moving object based on its previously determined position and the output from the INS. The accuracy with which these systems autonomously solve the navigation problem defines their grade. Any other method to define the class of the inertial sensors may lead to confusion. Accordingly, IMUs and INS, along with related inertial sensors, fall into four distinct grade categories: marine, navigation, tactical and automotive.

Marine-Grade 

Purpose and accuracy: Marine-grade INS, representing the highest performance category, are designed to provide extremely accurate standalone navigation solutions. They maintain an error margin of less than 1 nautical mile (approximately 1852 m) over a day. 

Applications: Used primarily in ships, submarines and specific spacecraft, these systems are crucial for navigating over long distances where high precision is essential. 

Navigation-Grade 

Standard compliance and accuracy:
Navigation-grade INS/IMU must conform to the SNU 84 standard, which sets a maximum horizontal position drift of 1 nautical mile (or about 1.5 km in some standards) within the first hour of operation. 

Applications: Integral to commercial airliners and military aircraft, these systems ensure safe and efficient navigation, particularly in environments where external navigational aids might be limited. 

Tactical-Grade 

Short-term accuracy: Tactical-grade IMU/INS are designed for short-term navigation solutions, offering precise guidance with an error margin of 1 nautical mile for a brief period, typically ranging from a few to 10 minutes. 

Extended capability through integration: While they have limitations in long-term accuracy, integrating them with other systems like GPS, vision or LiDAR enhances their utility, extending their applicability in various fields. 

Sub-categories: It is also worth noting that tactical grade can be further divided into three sub-categories: low-end tactical grade, standard tactical grade, and high-end tactical grade. Low-end tactical grade typically offers accuracy that is an order of magnitude lower than standard tactical grade. Conversely, the high-end tactical grade, sometimes referred to as near-navigation or low-end navigation grade, bridges the gap between standard tactical and navigation grades in terms of accuracy. 

Automotive-Grade 

Limited standalone capability: As the lowest grade, automotive-grade IMUs are not adequate for precise standalone navigation but are useful when combined with other systems. 

Alternative applications: They find use in attitude and heading reference systems (AHRS), pedestrian dead reckoning, and other auxiliary navigation systems, contributing significantly to vehicular technology. 

By adhering to this proposed classification system based on navigation accuracy, we can more accurately assess the capabilities and limitations of various IMUs and INS. This approach simplifies the process of selecting the right system for specific navigational needs and ensures the classification is directly tied to the core function of these systems. Thus, when determining the class of an inertial sensor, the direct and primary criterion should be the level of accuracy it provides in an autonomous navigation system. This original classification serves as a primary source, offering a clear and unequivocal framework for understanding and categorizing inertial sensors. 

Are Other Grades Needed?

Over the past decade, there has been a notable trend toward using inertial sensors in conjunction with correctors, such as LiDAR and visual odometry, excluding correctors that determine absolute coordinates like GPS. Fusing IMUs with non-inertial sensors enables the calibration of most (but not all) sensor errors. For example, in an ideal case, inertial sensor biases can be calibrated to the level of bias instability and INS attitude and position error can be determined by the level of angle random walk (ARW), velocity random walk (VRW), and bias instability. 

Consequently, this approach can elevate an automotive grade IMU’s navigation solution to tactical grade accuracy, or a tactical grade IMU to navigation grade accuracy. The final accuracy achieved by the IMU when fused with non-inertial correctors is predominantly determined by the quality of the correctors and estimation filters (which are not the focus of this discussion), but also by certain parameters of the inertial sensors themselves. 

In this context, it makes sense to establish a new terminology. If the parameters of the sensors (such as ARW, bias instability, VRW) enable an inertial system when fused with non-inertial correctors (excluding GPS) to achieve a certain level of performance, we could then refer to the sensor as having “In-Run [Specific Grade]” quality. For example, if an automotive-grade IMU, when combined with non-inertial sensors, achieves a performance of 1 nautical mile accuracy after 10 minutes, that IMU could be termed an “In-Run Tactical Grade IMU.” This classification recognizes the enhanced capability resulting from sensor fusion, thus offering a more nuanced view of the sensor’s performance in practical applications. 

Conclusion

This article does not introduce new information, as all the details discussed are well-established and readily available in numerous public domains. The primary objectives of this article are threefold. First, it encourages readers to engage with existing inertial navigation standards, highlighting their significance in the field of inertial sensor technology. Second, the article draws attention to the fact that, occasionally, these standards are not interpreted correctly, leading to inconsistencies in application and understanding. Finally, the article aims to initiate a dialogue regarding the necessity of a new standard for defining sensor grades. By posing this question, the author seeks to provoke thoughtful consideration and discussion within the industry, with the goal of refining and enhancing the standards that guide our understanding and use of inertial sensors. 

Author

Sergey Zotov, Ph.D., is a Chief Scientist and EMCORE Fellow with 20 years of experience in developing inertial navigation products. He specializes in advancing the technology of quartz MEMS inertial sensors. Additionally, he has expertise in simultaneous localization and mapping (SLAM), computer vision and sensor fusion.

The post The Inertialist: Do We Need Another Standard? appeared first on Inside GNSS - Global Navigation Satellite Systems Engineering, Policy, and Design.

Fruition is a word that comes to mind when examining the life and career of Steve Woolven. Experiences at an early age, at work and at school, left significant and lasting impressions, preparing him for a ground-breaking career in the research, development and commercialization of inertial positioning technology.

First, the Backdrop

“I was born in Toronto, Canada,” Woolven told Inside GNSS, “and then, as an infant, I moved to Ottawa, the capital, with my parents. I can remember as a kid the snowbanks being so high by February that you could stand on them and touch the eavestroughs of the roof.” He was already reaching for the sky. “Things like that stick out,” he said. “We lived in Ottawa until I was about 12, and then moved back to Toronto.”

Young Woolven grew up playing football, Canadian football, which is very similar but not identical to American football. “The Ottawa Rough Riders were my favorite team,” he said. “I still watch the Canadian Grey Cup.”

By the time he got to high school, his career had taken an academic bent. Both his parents were very supportive of his scholarly endeavors, and that meant a lot to him, but his hands-on involvement in the family business had an equally telling impact. “My dad was an entrepreneur and was quite proud of his real estate business,” Woolven said, “but they also ran a family resort, with cottages that we rented out. It was an idyllic place. I remember we had just one phone out there, and it was a party line, so people could come up and just literally drop off the grid.”

Seeds Sown

“My dad was occupied running two businesses, so by the time I was 14, maybe 15, he basically handed me the reins of the family resort. I ran it, with my younger sister, with my dad as a backstop.”

The fact his father trusted him to take on the job says something about young Woolven’s character. His responsibilities included looking after the guests, and much more. “I learned to do all kinds of repairs,” he said, “plumbing, electrical and outboard engines. We worked with tractors, launching boats, cutting hay, grading roads, so I got a pretty wide set of experiences, and learned to be self-sufficient.”

It was about problem solving: “You had to do a lot of thinking on your feet,” Woolven said, “when you had guests standing at the door with a hot water tank that was leaking, or a boat motor that wouldn’t start.”

And about good business: “I guess today we would talk about the customer success perspective; if you do a good job, the guests come back, and they came back year after year. We were tremendously successful at getting repeat customers. Today, we refer to this as recurring revenue. We didn’t use that term back then, but that’s what it was.” And that was something Woolven would remember.

The Academic

Unsurprisingly, the president of a highly innovative technology firm was interested in math and science as a student, but also history, and he credits a tough Grade 13 English teacher with instilling in him an appreciation for the written word.

Woolven became the first in his family—though not the last; he was followed by his younger sister—to graduate from university. He earned undergraduate and graduate degrees in engineering, including a doctorate, from the University of Toronto.

“As an undergrad I did a program called Engineering Science. It was a mix of pure sciences, two years of heavy physics and math, and then four years of engineering specialization crammed into the last two years. It was a tough undergraduate degree, hugely broad, from general relativity, special relativity to thermodynamics, and then all the engineering courses. And we had a terrific group of people, some of whom I still run across in business today.”

In grad school, he was all about integrated optics, blending lightwave theory in physical optics with electronic digital signal processing. “At the time, it was pretty leading-edge stuff,” he said, “and to some extent it still is, and from day one my goal was to come out of university with a Ph.D.”

“We were working under contract with one of the Canadian defense research institutes,” he recalled. “My thesis was around developing an optical computer for real-time target detection and recognition. Woolven did a master’s and then a Ph.D. in accelerated style. He was zeroing in on his true calling, though he didn’t know it yet.

“That was really good practice for later commercial and industrial experience,” he said. Indeed. “We faced the same kind of challenge when I joined Applied Analytics [now Applanix],”Woolven said, “where we wanted to take the research, IP technology, something that you can demonstrate on a bench, and move it into the field in a reliable product, something a customer can use to actually solve a problem.”

But we’re getting ahead of ourselves. Woolven first had to make the big move. “The fact is, I had my mind set on a career in academia. I loved the research and teaching and that’s what I wanted to do.”

From College to Applanix

“The next step for me was post Ph.D. research work at U of T, extending the research I’d already done, while also lecturing graduate students. One of the people I was doing research with at the defense institute happened to be sitting across the hall from another researcher who was working with the founders of a new start-up. These were the Applied Analytics founders, Blake Reid, Erik Lithopoulos and Bruno Scherzinger. The person I knew thought I should meet them. Of course, I didn’t know a thing about them. And I couldn’t Google them.” It was the early 90s. “They’d come out of Honeywell’s Advanced Technology Center, here in Canada, and had won several defense research contracts, doing integrated navigation for industrial applications.”

Woolven set up an interview with Reid and learned they had a story and a vision. “The dream was inspiring,” he said, “to take a technology developed for defense applications and move it into the industrial space, the professional survey and mapping space. I remember leaving the interview, calling my wife and saying—”

What a minute. Wife? We missed something here, but we’ll catch up with that half of the story later.

“—calling my wife and saying, ‘I don’t know if these guys have a hope of succeeding, but this looks like it could be a really fun ride.’” Woolven joined Applied Analytics full time in 1992 as employee No. 8.

That first Applied Analytics Technology

“The company was using inertial technology, GNSS technology and other sensors to create what we now call a sensor fusion engine,” Woolven said. “In other words, it was the grandfather of the technology that is in all Applanix products to this day. It was a big five-foot rack back then, what the first fielded Applanix POS systems came out of, written in Ada. They were using it as a benchmark to test the accuracy of new helicopter navigation systems, and also in underwater towed body research, using acoustics to look for—you can guess what they were looking for—undersea bodies that are bigger than a bread box but smaller than a car.”

As the company grew, Woolven went from research engineering to industrial engineering to project manager and eventually became head of engineering. But the company still had a way to go. “We were a bunch of really smart engineers,” he said, “but when it came to understanding what the market needed, we probably thought we knew more than we did.”

The company made a series of thoughtful moves, bringing in key personnel, with the right experience and perspective, who would ultimately help to transform the business. Dieter Zeuner joined Applanix out of Zeiss, formerly in East Germany, and helped the company understand the pathway into the aerial photogrammetric market. “Dieter led us down the path of taking this technology and making it work in the digital photogrammetric space and the brand new aerial LiDAR space,” Woolven said. “And on the marine side, we partnered with Roger Hutchins, who helped us understand the marine hydrographic segment.

“These individuals knew what the problems were that needed to be solved in the real world. They understood the hardware we needed to work with and most importantly the customer workflows. We needed that practical knowledge. Without it, I don’t think we would have been anywhere near as successful as we ultimately have been.”

There was something about Applanix, a certain, dare we say, “magic,” and the world of surveying and mapping was starting to feel it.

The Trimble Affair

By the late 1990s, Applanix was growing rapidly. “We had inertial technology down pat,” Woolven said, “but in order to push the performance and drop cost, we needed to get access to GNSS. Not just the boards, but to get into the actual IP of GNSS. We also knew that Trimble had great technology and great access to markets, customers and distribution.”

To be sure, anyone who was around at the time knew Trimble was a big-time navigation and positioning company that had its act together. Discussions ramped up between the two companies in early 2003, and by July of that year, Trimble was able to announce that it had agreed to acquire Applanix, and the rest, as they say, is history.

“The intent was always to bring Applanix technology into the Trimble fold,” Woolven said, “so that our sensor fusion engines would become available right across the Trimble product line, and then to build, to integrate their GNSS with our aided inertial technology.” The first generation of tightly coupled technology, after the acquisition, was dubbed, for internal purposes, mPOS.

Applanix was already known as a premium, high-end brand. “Our products tended to live in the upper end of the price points,” Woolven said. “After the acquisition, we worked to build out our portfolio, to service customers from entry level requirements right through to high end products, and we’ve continued to push that barrier.

“Our technology has demonstrated the ability to work in really difficult GNSS or GNSS-denied areas,” he said. “Of course, open-sky technology is important, but anybody can do GNSS in the middle of a farmer’s field. It’s a different story once you get into more complex, urban environments. It took a lot of hard work. We did testing in downtown San Francisco, for example, which is a nightmare for GNSS, and in many ports and harbors, where you’re in and around bridges, large vessels, big cranes overhanging, constantly causing GNSS occlusion. It was those kinds of issues that we couldn’t solve without tightly coupled algorithms. Then, to be able to take the technology into difficult areas, holding accuracy for a longer period of time, or giving you high-accuracy, direct georeferencing data, at a price point that makes sense for your business model; that was really the game changer.”

What’s That Magic?

“One of the things that makes us special is the way we serve our customers, being there when they need us and finding solutions,” Woolven said. “Having great technology is crucial, but it’s the ability to provide the whole product, from the hardware to the post-processing software, and Trimble RTX®, which is our advanced precise point positioning technology, and then we bring our entire customer success organization, where, when the customer has a problem, say you’ve got a survey vessel sitting at the dock or an airplane sitting on the tarmac and it can’t take off. We’re able to support those customers, walk them through things, whatever it needs, to limit their downtime.

“And then, we’ve had those true visionaries, Dieter, Roger, Erik Lithopoulos, who could actually see that the industry was changing, moving toward digital photogrammetry, for example, knowing that LiDAR scanning wasn’t going to work without direct georeferencing. It’s about knowing what those new businesses are going to need, and mapping out what the end game is going to look like. Then you can bring that vision back to engineers, so we can go away and develop it.”

Today, many people think of Applanix as a hardware company, and it still is that, but Woolven said it’s much more. “We’re good at making hardware, but that’s not really our core IP. What we do is make algorithms that solve people’s problems. We code them up, make embedded firmware, desktop and cloud software, and that, married with the hardware, is what makes the magic happen. It’s the application of those algorithms to solving people’s real-world problems. That’s what we’re really good at.”

Better Than Ever

Woolven has continued to work to move Applanix into new markets, like the UAV market. “We launched the Trimble PX-1 RTX, targeting commercial drone navigation,” he said. This is the much lauded, robust, centimeter-level, continuous GNSS-inertial positioning engine with over-the-air Trimble CenterPoint® RTX correction service.

“It’s meant a different approach to our customers in that market,” Woolven said. “Rather than a single-sale type of product, it’s more like a cell-phone business model, where you buy the hardware for a small amount of money, it gets integrated into the UAV, and then you buy the capability you need, depending on what type of job you’re flying, whether that’s a single-base type solution, or you might want to use CenterPoint RTX technology…It allows our customers to tailor their own business models so that the costs fit the projects they’re trying to do.”

All that attention paid to customers, understanding their issues, solving problems on the fly and keeping everybody happy, sounds kind of like running a family holiday resort as a teenager in Canada. “There was less sensor fusion back then,” Woolven said.

No Place Like Home

Woolven still lives in Toronto, where he has been and remains a family man. It was his wife, readers will recall, in whom he confided, all those years ago, when it was time to decide on his pathway forward.

“My wife has just as many degrees as I do,” Woolven said. “She’s a medical doctor, currently chief of Family and Community medicine at one of the downtown Toronto hospitals, so she’s got a few things on her plate. She’s a well published author and was just recognized as the family medicine physician of the year here in Toronto. She’s pretty accomplished and I’m pretty proud of her.”

The results of this stellar union were, among other things, two children, a boy, now 28, and a girl, now 25, who just graduated with a master’s degree in Psychotherapy. “We had our hands full when the kids were young, two kids, two dogs and two active careers. But we made it run by working as a team,” Woolven said.

Woolven’s mother passed away several years ago, but his father, now 90, remains the rock-solid foundation of the Woolven line, and he still enjoys keeping young Woolven on his toes. “We still go out hiking,” Woolven said. “Not too long ago we went out to hike Zion National Park in Utah, like we used to do when I was younger. This time we took my son, so we had three generations raising dust out there.” To celebrate his dad’s 90th, in 2023, Woolven took the family up to the Muskokas, near Georgian Bay, for another week of hiking. It seems you can’t keep those Woolven boys down.

The old family resort is still there, now under a different owner, the senior Woolven having sold it some 20 years ago. The descendants of some of the guests Woolven used to serve still come back every year. Credit his own proficiency in attending to their needs. No doubt management of the place has suffered since he ran it as a boy, but his attention was needed elsewhere. We think he’s kept the place with him, in his heart and in his head, the whole time. He’s worked his own kind of magic to help turn Applanix into a very successful concern. Fruition, we said. Fruition, indeed.

The post Human Engineering: Making the Magic Happen appeared first on Inside GNSS - Global Navigation Satellite Systems Engineering, Policy, and Design.

SAHANA BANDAGADDE UMESHA, THOMAS KRAUS, NIKOLAS DÜTSCH, DR. CLOVIS MAIA, PROF. THOMAS PANY INSTITUTE OF SPACE TECHNOLOGY AND SPACE APPLICATIONS, UNIVERSITÄT DER BUNDESWEHR, MUNICH

This technology is crucial for many missions, especially in improving navigation systems. However, the rising threat of radio frequency (RF) jamming hinders LEO satellite missions that rely on precise positioning. Given this context, it is vital to consider the following questions: Are space receivers most at risk from jamming? How does jamming affect space receiver reliability? What mitigation techniques are available? 

Recent advancements, noted as of late 2021, have expanded interception capabilities to include operations from the Earth’s surface, as detailed in [2]. These technologies also can disrupt LEO satellites’ RF communications by deploying mobile platforms. It’s clear jamming GNSS signals is emerging as a significant threat. A comprehensive analysis of space receiver jamming is presented in [3] and delves into techniques designed to enhance the robustness of receiver tracking loops, thus mitigating the adverse effects of jamming while maintaining precise positioning capabilities. Expanding upon [3], this article thoroughly examines jamming effects on a space receiver, focusing on factors like antenna pattern and link budget. It is closely tied to the ongoing development of Seamless Radio Networks for Internet of Space (SeRANIS) [4], a LEO satellite mission at the University of the Bundeswehr, Munich.

Small Satellite Missions and the Need for Jamming Mitigation

The SeRANIS satellite plays a pivotal role in various research domains, such as space communications that include broadband communications and Internet of things (IoT), radio science, high-level AI-based autonomy, GNSS technologies (occultation, reflectometry and jamming/spoofing monitoring), optical and IR Earth observation as well as object detection algorithms, payload operation concepts, modern structures, innovative system-health-monitoring techniques, and electrical-propulsion [5]. These applications rely heavily on GNSS for precise positioning, navigation and timing (PNT). By incorporating jamming mitigation technology, these small satellites can ensure uninterrupted access to accurate location/timing data even in challenging environments where jamming attempts may occur. This capability enhances the reliability and effectiveness of small satellite missions, enabling them to fulfill their objectives with greater resilience and efficiency [5]. 

Understanding SeRANIS: Mission-Specific Details

The SeRANIS satellite is called ATHENE 1 and epitomizes a leading-edge advancement in LEO research, distinguished by its intricate technical specifications finely tuned for scientific exploration. With a payload capacity of 75 kg and a takeoff weight of 200 kg, it features a versatile platform capable of accommodating a diverse array of more than 15 meticulously designed research experiments. Operating at an altitude of approximately 550 km, ATHENE 1 executes precise orbital maneuvers, facilitating the acquisition of vital data essential for understanding intricate phenomena. Its operational lifespan of five years ensures sustained observation periods, enabling comprehensive critical studies for advancing the understanding of space dynamics.

This research benefited from the imagery shown in Figure 1 courtesy of LuxSpace [6], a prominent satellite provider, augmenting the authenticity and visual impact of our work.

The orbital parameters crucial for understanding the satellite’s trajectory and mission profile, particularly within its Sun Synchronous Orbit, are provided in Table 1. In the current phase, the satellite possesses two sets of orbital parameters (options A and B). These alternatives will undergo evaluation and selection processes to determine the optimal configuration for the mission’s objectives.

Jamming Scenario 

Given its widely acknowledged status, jamming relies on power and spectral occupancy to disrupt GNSS signals. Following this, RF interference can further be divided into other categories such as chirp jamming, spoofing, matched code interferers and many others [7]. Monitoring the interference from LEO satellites instead of terrestrial receivers provides the unique Earth viewpoint, with a global perspective on the interference patterns in a high resolution. 

The focal point of the respective SeRANIS experiment shown in Figure 2 revolves around a system designed to detect and localize terrestrial interference signals, with a particular emphasis on identifying jamming within the L1/L5 frequency range. The payload can be assigned the task of gathering raw IQ/IF data, making it possible to conduct RF spectrum monitoring within the L-band (L1 and L5). 

This system consists of three main components (i.e., three different receivers/recording units connected to zenith and nadir antennas). As illustrated in Figure 3, the SeRANIS satellite comprises three distinct antennas, consisting of two zenith-facing antennas and one nadir-facing antenna, each linked to individual receivers/recording units. The recording system (Number 3) receives possible interference signals from the nadir-oriented antenna. The system samples the RF input signal and stores the IQ data in the internal memory. The IQ data signal contains the interference signal, which is transferred toward the ground station via the X-band communication link. In post-processing, with the help of software tools developed at the institute, these signals are further analyzed to geo-locate and extract the interference source. The recording system samples the RF input signal of the zenith-oriented antenna 1 and stores the IQ data in the internal memory. After downlinking the raw data, the institute’s GNSS software receiver (MuSNAT) [8-10] processes the data stream. Furthermore, it can be configured to apply diverse jamming mitigation strategies.

In this article, emphasis is placed solely on interference signal reception at zenith-facing antennas, as additional noise-like signals may superimpose the authentic GNSS signals and degrade the performance of the PVT solution at the satellite during post-processing analysis. PVT unavailability or a degraded PVT solution will negatively impact the ability to localize the jammer. Consequently, our study centers on leveraging the capabilities of Recording System 1 in combatting the effects of jamming. The up-looking 
zenith-oriented antenna 1 employed in the satellite comprises an L1/L5 patch antenna design [11]. With a bandwidth of 20 MHz and a -3 dB beamwidth spanning 90°, it is meticulously engineered to optimize reception efficiency while ensuring broad coverage to the GNSS constellation.

Zenith antenna 2 and the space-qualified GPS receiver are completely under the responsibility of the satellite platform provider LuxSpace. It is out of the scope of the analysis for this article, but it is noted the space-qualified GPS receiver chosen for the SeRANIS satellite provides accuracy with <10 m position and <20 cm/s velocity (1-sigma), operating at a 1 Hz update rate in LEO.

Simulation Environment

A simulation of the SeRANIS satellite’s sun-synchronous orbit employing Keplerian elements, as specified in Table 1 Option B, was initiated to create a jamming scenario at the zenith antenna. This article introduces a simulation environment. It elucidates a geometric relationship between a satellite and an emitter with a focus on modeling received interference power at the satellite’s zenith antenna. The framework incorporates link modeling, free-space-loss calculation, azimuth, elevation angle determination of the incoming wave at the satellite, and zenith antenna pattern modeling to consider different gains at different azimuth and elevation angles. By integrating these elements, the simulation enables accurate analysis of the received power during a single overflight. The satellite plaform’s ground-based RF interference shielding is modeled by (a) simulating a ground plane and (b) taking a choke ring antenna pattern from the literature. Both yielded consistent results.

The web map (Figure 4) presents the SeRANIS satellite trajectory alongside an emitter’s location. It highlights potential interference sources that could disrupt satellite navigation signals, aiding in vulnerability assessment against jamming attacks. 

With the aid of a Satellite Communications Toolbox [12] in MATLAB R2023a [13], and considering the orbital parameters, the primary observables of identified interference measured within the delay-Doppler domain include distance, angle of arrival, azimuth, and elevation data, which shall be used to establish the link analysis. 

Noise Environment

Naturally present thermal noise parameters such as receiver noise bandwidth (B), noise power density (N₀), and the components’ noise figure (band pass filter, LNA and mixer) are considered and listed in Table 2. They represent the degradation in the SNR from internal noise sources. The noise power density can be calculated based on:

where k is the Boltzmann’s constant (1.380649×10-23 J.K-1), and T is the temperature in Kelvin (268.15K).

Before proceeding with the link budget analysis, it is imperative to evaluate the Right-Hand-Circular-Polarized (RHCP) simulated antenna radiation pattern of the updated version of the scarabaeus antenna employed on the SeRANIS satellite (red curve) and measured radiation pattern of a GPS antenna installed atop a NovAtel Model 503 choke ring [14] with ground-plane (blue curve) as displayed in Figure 5. The SeRANIS antenna was simulated with a ground-plane for the single element with a size of 150×150 mm² [11]. This comparative analysis is critical as it provides insights into the antenna’s directional characteristics and how they are influenced by the presence of a ground plane mimicking the satellite platform. For comparative purposes with the SeRANIS antenna, the normalized gain values of the ground-plane antenna in [14] were augmented by an additional 8.5 dB. The antenna pattern illustrated demonstrates a significant decrease in gain below the horizon.

In the radiation patterns, the maximum gain is usually observed at the peak of the main lobe, which is at zero degree, corresponding to the zenith direction in this case. Please note the 180° elevation in the antenna radiation pattern (Figure 5) corresponds to the -90° in the elevation profile (Figure 7). The asymmetry in the pattern at negative elevation angles (90 to 270°) can arise from factors such as antenna design, mounting effects, and electromagnetic interference. 

Figure 6 depicts the distance between the emitter and the satellite, while Figure 7 shows the elevation angle of the incoming wave at the satellite. These plots serve as reference points for understanding subsequent plots detailing variations in C/N₀ and received power. Notably, around 8 minutes into the scenario, the satellite is as close as 566.8 km to the emitter at the zenith (i.e., at -90 deg). 

Figure 8 investigates the impact of varying emitter power levels on received RF power within a GNSS receiver. At an emitter power of 350 kW, the maximum received power reaches -127 dBW, contrasting with the minimum received power of -136 dBW at the zenith. Considering the RF front end, no degradation is expected through hardware with the given emitter power level of 3.5 kW, 350 kW and 3,500 kW. The maximum received power level from the zenith antenna is -118 dBW. The LNA used for the satellite mission is the CMA-162LN+ from Mini-Circuits, which has a 1-dB compression point for an output power of 18.8 dBm. The gain of the LNA is 19.1 dB, which results in the 1-dB compression point input power of -0.3 dBm or -30.3 dBW. The LNA will never saturate with the received power levels. Even the signal dynamic of the front end is only slightly increased by the interference. The noise at the receiver input from Table 2 is -129.2 dBW in the worst case of 33°C receiver noise temperature. This leads to an increase in the signal dynamic of 11.2 dB. The used converter is a Σ-Δ ADC, which achieves at least 14 bits of resolution. This ADC is integrated into the dual RF transceiver AD9371 from Analog Devices.

The variation in the carrier-to-noise density ratio is calculated based on the Q factor and other parameters: 

Figure 9 illustrates how the C/N₀ would vary for distinct levels of transmitted power (PRF) i.e., 3.5 kW, 350 kW and 3500 kW (EIRP), and a noise power spectral density (N0) of -202.8 dBW/Hz. The dips in the curve indicate reduced signal quality due to decreased distance, aligning with the emitter’s position. It is worth noting the impact of interference is most prominent in the periods immediately preceding and following the satellite’s traversal of the zenith, rather than during its direct passage above the zenith. This observation underscores the temporal dynamics of interference effects on the carrier-to-noise ratio.

In addition to high emitter power levels, a very low emitter power level of 3.5kW inducing a C/N₀ degradation of 1 dB was considered. As mentioned in [15], the use of 1-dB decrease in carrier-to-noise density ratio (C/N₀) as the appropriate interference protection criterion (IPC) for GPS and other Radionavigation Satellite Systems (RNSS). [15] provides a brief explanation of the relationship between a (post-correlation) 1-dB drop in C/N and an interference-to-noise ratio (I/N) of–6 dB. 

In typical operational GNSS space contexts, tracking thresholds are established at C/N₀ levels near 25 dB-Hz. Considering a scenario with a nominal GNSS signal strength of 40 dB-Hz, coupled with a 25 dB interference loss, the receiver encounters a significant challenge in achieving robust tracking. Under these conditions, such a space receiver becomes more vulnerable to experiencing loss of lock in both code and phase domains, indicating a notable lack of resilience.

How can we mitigate the impact of interference on receiver performance?

Given the possibility of a very large emitter power of 3.5 MW and the consequent degradation of signal strength of 25 dB, SeRANIS may not continue to provide reliable positioning results. However, it is possible to implement robust tracking loops, allowing the receiver to provide continuous and accurate positioning results.

The principal objective of external aiding lies in acquiring velocity data by predicting the satellite’s orbital motion, which holds significant importance in carrier tracking with a diminished loop bandwidth (PLL bandwidth). By converting this velocity data into the line-of-sight, it becomes feasible to establish a Carrier-Doppler aiding in each channel, thereby delineating the line-of-sight domain between the user and the satellite. This Doppler-assisted carrier information can then be employed for code tracking, a phenomenon called Carrier-Doppler-aided Code tracking [16]. From [3], it is proven that incorporating Doppler aiding enhances the receiver’s resilience against interference and jamming. It is worth noting the SeRANIS satellite employs a very stable clock (a so-called ultra-stable oscillator) so the effects of clock jitter can be neglected. 

As proof of this mitigation technique, Figure 10 shows the positional accuracy (comparing the position of SeRANIS under the event of jamming with a reference trajectory serving as ground truth) in the case of a completely unaided tracking loop. Figure 11 illustrates the obtained positional accuracy under the implementation of a Carrier-Doppler-aided code tracking loop. This comparison occurs under the case of a completely aided tracking loop, demonstrating both robustness and “dm-level” accuracy in the obtained position. In principle, this is a sophisticated tracking mechanism that capitalizes on carrier frequency information to counteract Doppler effects, thereby improving the precision and reliability of code tracking in various dynamic communication and navigation systems. A comparative analysis of various aiding mechanisms is provided in [3].

In addition to the outlined strategies, other mitigation measures exist for SeRANIS concerning signal filtering and/or nulling interference based on both LHCP and RHCP signals from zenith antenna 1.

Conclusion and Future Direction

This article delves into the critical realm of defending space-based receivers against jamming attacks, particularly focusing on interference within the GPS L1 frequency range for one of the ATHENE 1 satellite’s zenith antennas.

A small simulation framework provided valuable insights into the challenges posed by jamming attacks and verified the single-satellite single-pass over an emitter and processing the jamming signals in a GNSS receiver with the implementation of a Carrier-Doppler-aided Code tracking loop. The developed technique to mitigate the adverse effects of jamming has been proven to provide a higher degree of robustness as well as more accurate receiver positioning. The receiver exhibited robustness by converging to decimeter-level accuracy within the predicted 20-second convergence time. Notwithstanding, it remains necessary to ascertain whether these outcomes remain applicable when accounting for atmospheric effects and other sources of error in the simulation.

Looking ahead, further research endeavors could explore enhanced mitigation strategies to bolster resilience against jamming attacks. By continuing to advance our understanding of space-based interference detection and mitigation, we can fortify the integrity and reliability of GNSS services, ensuring their indispensable role in modern navigation systems. 

Acknowledgements 

This research is funded by dtec.bw– Digitalization and Technology Research Center of the Bundeswehr SeRANIS.

References 

[1] E. Gill, J. Morton, P. Axelrad, D. M. Akos, M. Centrella, and S. Speretta, “Overview of Space-Capable Global Navigation Satellite Systems Receivers: Heritage, Status and the Trend towards Miniaturization,” Sensors, vol. 23, no. 17, Sep. 2023, doi: https://doi.org/10.3390/s23177648.

[2] Donatas Palavenis, “Moscow develops military space tech: should we take note? – analysis – LRT.” Accessed: Feb. 16, 2024. [Online]. Available: https://www.lrt.lt/en/news-in-english/19/1570739/moscow-develops-military-space-tech-should-we-take-note-analysis

[3] Sahana Bandagadde Umesha, Clovis Maia, Mohamed Bochkati, Jürgen Dampf, and Thomas Pany, “A Pre- and Post-correlation Comparative Analysis to Assess Resilience Against Jamming for GNSS Space Receivers,” presented at the 36th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2023), Denver, Colorado, pp. 1544–1564.

[4] “SeRANIS – Multifunctional Satellite Laboratory | UniBw M | dtec.bw.” Accessed: Feb. 16, 2024. [Online]. Available: https://seranis.de/en/home-en/

[5] A. Kinzel et al., “Seamless Radio Access Network for Internet of Space (SeRANIS): New Space Mission for Research, Development, and In-Orbit Demonstration of Cutting-Edge Technologies,” in 73rd International Astronautical Congress (IAC), Paris: International Astronautical Federation (IAF), Sep. 2022. [Online]. Available: https://athene-forschung.unibw.de/85049?query=Knopp+F%C3%B6rstner&show_id=143331

[6] “LuxSpace -OHB Digital.” [Online]. Available: https://www.ohb-digital.de/expertise/firmen/luxspace

[7] Z. Clements, T. E. Humphreys, and P. Ellis, “Dual-Satellite Geolocation of Terrestrial GNSS Jammers from Low Earth Orbit,” presented at the 2023 IEEE/ION Position, Location and Navigation Symposium (PLANS), Monterey, CA, USA: IEEE, Apr. 2023. doi: https://doi.org/10.1109/PLANS53410.2023.10140058.

[8] “MuSNAT (Multi-Sensor Navigation Analysis Tool).” Institute of Space Technology and Space Applications (ISTA), Universitaet der Bundedswehr Muenchen (UniBwM). Accessed: Apr. 08, 2024. [Online]. Available: https://www.unibw.de/lrt9/lrt-9.2/software-packages/musnat

[9] T. Pany et al., “The Multi-Sensor Navigation Analysis Tool (MuSNAT) – Architecture, LiDAR, GPU/CPU GNSS Signal Processing,” in The Insitute of Navigation (ION GNSS+), Miami, Florida, Sep. 2019, pp. 4087–4115. doi: https://doi.org/10.33012/2019.17128.

[10] M. Arizabaleta et al., “Recent Enhancements of the Multi-Sensor Navigation Analysis Tool (MuSNAT),” in The Institute of Navigation (ION GNSS+), St. Louis, Missouri, Sep. 2021, pp. 2733–2753. doi: 10.33012/2021.17960.

[11] The MathWorks Inc., “Satellite Communications Toolbox.” The MathWorks Inc., Natick, Massachusetts, United States. [Online]. Available: https://de.mathworks.com/products/satellite-communications.html

[12] The MathWorks Inc., “MATLAB.” The MathWorks Inc., Natick, Massachusetts, United States. [Online]. Available: https://www.mathworks.com

[13] B. R. Rao, W. Kunysz, R. Fante, and K. McDonald, GPS/GNSS antennas. in Artech House GNSS technology and applications series. Boston London: Artech House, 2013.

[14] A. Meredov and S. Lindenmeier, “Circular Polarized Compact Dual Antenna Set for L-Band Space Applications,” presented at the Proceedings of the 53rd European Microwave Conference, Sep. 2023. doi: 10.23919/EuMC58039.2023.10290276.

[15] U.S. Air Force, “Background Paper on use of a 1-dB Decrease in C/N0 as GPS Interference Protection Criterion.” [Online]. Available: https://www.gps.gov/spectrum/ABC/1dB-background-paper.pdf

[16] Jong Hoon and T. Pany, “Signal Processing,” in Handbook of Global Navigation Satellite Systems, Springer, 2017, pp. 401–442. [Online]. Available: https://doi.org/10.1007/978-3-319-42928-1_14

Authors

Sahana Bandagadde Umesha works as a research associate at the Institute of Space Technology and Space Applications of the University of the Bundeswehr Munich. Her research activities include GNSS receiver technology, interference analysis, and aiding mechanisms for space receivers. She holds a master’s degree in Earth Oriented Space Science and Technology (ESPACE) from the Technical University of Munich, Germany.

Thomas Kraus is a research associate at the University of the Bundeswehr Munich and works for the satellite navigation unit LRT 9.2 of the Institute of Space Technology and Space Applications (ISTA). His research focuses on future receiver design offering a superior detection and mitigation capability of RF interferences. He has a master’s degree in electrical engineering from the Technical University of Darmstadt, Germany.

Nikolas Dütsch is a research associate at the University of the Bundeswehr Munich and works for the satellite navigation unit LRT 9.2 of the Institute of Space Technology and Space Applications (ISTA). His research focuses on the sensitive detection and geo-location of RF interference sources from low-Earth-orbit (LEO) satellites. He holds a master’s degree in electrical engineering from the Friedrich-Alexander-University of Erlangen/Nuremberg, Germany.

Dr. Clovis Maia has worked as a research associate at the University of the Bundeswehr Munich since 2022, where he has worked with software defined receivers for GNSS signal processing and positioning under electronic warfare conditions, as well as hybrid PNT technology with the use of LEO satellite constellations.

Prof. Thomas Pany is a full professor at Universität der Bundeswehr München at the faculty of aerospace engineering where he teaches satellite navigation. He focuses on GNSS/LTE/5G signal design and processing, software receivers and GNSS/INS/LiDAR fusion. He has about 200 publications including patents and one monography.

The post Navigating the Noise: Space Receivers Defending Against Jamming Attacks appeared first on Inside GNSS - Global Navigation Satellite Systems Engineering, Policy, and Design.

DAVID GABER, GROUP PRODUCT MANAGER, INERTIAL SENSING DEVICES, EPSON

In the development of systems requiring inertial measurement technologies for high performance applications, the choice between quartz MEMS and silicon MEMS inertial measurement units (IMUs) is crucial for achieving optimal performance and reliability. This article examines the advantages of quartz and silicon MEMS IMUs in critical scenarios, addressing their respective stability, precision and resilience. Additionally, it delves into the compensatory measures employed by silicon MEMS IMUs to mitigate inherent performance limitations and explores the tuning capabilities that allow skilled engineers to optimize both types of MEMS IMUs for specific application requirements. In both cases, if customers are seeking high performance MEMS IMUs and have skilled engineering resources at their disposal, there is a clear advantage to integrating MEMS IMUs from original equipment manufacturers (OEMs) versus integrators.

Key Parameters for Engineers Building High Performance Systems

Bias Stability: Bias stability refers to the stability of the IMU’s output when it is not experiencing any external acceleration or rotation. The bias represents a constant error in the sensor output that can cause drift in the navigation solution over time. Low bias stability is essential for maintaining accurate and stable navigation estimates, especially during periods when GNSS signals are unavailable or unreliable (e.g., in urban canyons or under dense foliage).

Noise Performance: IMU noise directly affects the accuracy of the derived navigation solution, particularly in the presence of low-frequency signals (e.g., gravity). Lower noise levels enable more precise measurement of accelerations and angular rates, resulting in improved navigation accuracy and reduced error accumulation during integration.

Scale Factor Stability: Scale factor stability refers to the consistency of the IMU’s sensitivity (scale factor) over time and environmental conditions. Variations in scale factor can introduce errors in navigation calculations, especially during dynamic maneuvers or changes in temperature.

Dynamic Range: The dynamic range of the IMU determines the maximum accelerations and angular rates that it can accurately measure without saturation. A wide dynamic range is crucial for accommodating various operating conditions and maneuvers encountered during navigation, ensuring the IMU remains within its linear measurement range.

Temperature Stability: IMU performance can be significantly affected by temperature variations, leading to changes in bias, scale factor and noise characteristics. Good temperature stability ensures consistent performance across different environmental conditions, reducing the need for frequent recalibration.

Alignment Accuracy: Accurate alignment of the IMU’s sensor axes with respect to the platform’s reference frame is essential for computing precise attitude (orientation) estimates. Misalignment errors can introduce significant errors in the navigation solution, particularly when GNSS aiding is intermittent or unavailable.

Update Rate and Latency: The IMU’s update rate determines how frequently new measurements are available for navigation computations. Low latency and high update rates are critical for real-time navigation applications, ensuring timely updates to the navigation solution and reducing the impact of dynamic motion on accuracy.

Advantages of Quartz MEMS IMUs

High Precision and Stability: Employing innovative sensor designs and packaging, quartz MEMS IMUs offer exceptional precision and stability, essential for navigation, guidance and control tasks in high performance applications.

Resilience to Harsh Environments: Using synthetic crystal grown specifically for inertial sensors, quartz MEMS IMUs exhibit inherent robustness against temperature variations, solar radiation exposure and persistent operation in low atmospheric pressure, ensuring consistent performance in challenging operational conditions.

Frequency Stability and Q Factor: Quartz inertial sensors in MEMS IMUs provide high Q factor and stable resonance frequencies, minimizing frequency variations and drift over time.

Limitations of Quartz as an Inertial Sensor Base Material

Despite their advantages, quartz MEMS IMUs have certain limitations:

Fragility: Quartz inertial sensing elements themselves can be fragile and susceptible to mechanical stress, requiring careful handling and protective measures before they’re installed in IMU packages. Quartz MEMS IMUs are often accompanied by specific handling instructions to minimize accidental damage risks during integration.

Delta Frequency Issues: Quartz MEMS IMUs may experience delta frequency shifts under specific conditions, affecting frequency stability. Continued exposure to vibration or shock at or near the delta frequency can also disrupt output accuracy.

Limited Performance at Very High Temperatures: At very high temperatures, quartz can undergo structural changes that affect its mechanical properties and stability. This limitation can restrict the use of quartz-based inertial sensors in extreme temperature environments.

Complex Manufacturing Process: Fabricat-ing high performance quartz-based inertial sensors involves complex manufacturing processes, including crystal growth and precision machining. These processes can be costly and may limit scalability and mass production of quartz inertial sensors into high-volume, commoditized applications like automotive safety or smartphone orientation.

Advantages of Silicon MEMS IMUs

Silicon MEMS IMUs offer several specific advantages that make them highly desirable for various applications, especially in automotive, robotics and consumer electronics. Some of the key advantages of silicon MEMS IMUs include:

Miniaturization: Silicon MEMS IMUs can be very small and lightweight compared to traditional inertial sensors, making them ideal for applications where size and weight constraints are critical, such as in drones, wearables, and handheld devices.

Low Cost: MEMS fabrication techniques allow for high-volume, cost-effective silicon MEMS IMU manufacturing. This makes them more affordable compared to traditional inertial sensors, enabling widespread adoption in consumer and industrial markets.

Low Power Consumption: Silicon MEMS IMUs typically consume very low power, making them suitable for battery-operated devices and applications where power efficiency is essential, such as in IoT devices and mobile platforms.

Integration: Silicon MEMS IMUs often integrate multiple sensors (gyroscope, accelerometer) into a single compact package. This integration simplifies system design, reduces component count, and improves overall system reliability.

Compensatory Measures in Silicon MEMS IMUs

Silicon MEMS IMUs leverage advanced signal processing and compensatory measures to enhance system performance:

Temperature Compensation: Silicon MEMS IMUs are sensitive to temperature variations, which can lead to changes in bias, scale factor and sensor output. Temperature compensation techniques involve measuring the IMU’s response at different temperatures and applying correction factors to minimize temperature-induced errors. Advanced algorithms and calibration methods are used to model and compensate for temperature effects, ensuring consistent performance across a range of operating temperatures.

Bias Drift Calibration: Bias drift is a common issue in IMUs, where the output bias slowly changes over time due to imperfections in sensor and environmental factors. To mitigate bias drift, silicon MEMS IMUs undergo regular calibration procedures to estimate and correct bias errors. Inertial navigation systems (INS) often employ Kalman filtering or similar algorithms to continuously estimate and compensate for bias drift based on IMU measurements and external sensor inputs (e.g., GNSS, magnetometers).

Scale Factor Calibration: Scale factor errors in Silicon MEMS IMUs can lead to non-linearities and inaccuracies in sensor measurements. Scale factor calibration involves characterizing the IMU’s sensitivity across its measurement range and applying correction factors to linearize the sensor response. Precise calibration techniques using controlled rotational tests and calibration standards are employed to optimize scale factor accuracy and reduce measurement errors.

Vibration and Shock Filtering: Silicon MEMS IMUs can be affected by external vibrations and shock, leading to transient spikes or noise in sensor readings. Filtering algorithms are implemented to remove or reduce the impact of high-frequency vibrations and shocks on IMU outputs. Digital signal processing techniques, such as low-pass filtering and adaptive filtering, are used to improve signal quality and enhance sensor robustness in dynamic environments.

Sensor Fusion with External Sensors: To improve accuracy and reliability, Silicon MEMS IMUs are often integrated with external sensors, such as GNSS receivers, magnetometers, and barometers, through sensor fusion algorithms. Fusion of IMU data with complementary sensor inputs allows for error compensation, enhanced navigation performance, and reliable orientation estimation even under challenging conditions (e.g., GPS signal loss or magnetic disturbances).

Dynamic Bias Compensation: Dynamic bias compensation techniques continuously monitor and adjust bias estimates based on real-time sensor data and environmental conditions. Adaptive algorithms adaptively estimate and correct bias errors, minimizing drift and improving the long-term stability of silicon MEMS IMUs.

Tuning Capabilities and Performance Extraction in Quartz and Silicon MEMS IMUs from OEMs

These are essential aspects that allow skilled customers to optimize sensor performance for specific applications. Here’s a detailed exploration of tuning capabilities and performance extraction:

Sensor Calibration: MEMS IMUs undergo calibration processes to adjust sensor outputs and minimize errors. Calibration involves compensating for sensor biases, scale factors, misalignments, and temperature effects. Customers can work with OEMs to specify calibration techniques to enhance sensor accuracy and reliability across operating conditions.

Parameter Adjustment: Customers can collaborate with OEMs to tune various parameters of MEMS IMUs to optimize performance. This includes adjusting sensor sensitivity, bandwidth, noise characteristics, and dynamic range based on application requirements. Parameter tuning allows customization to meet specific performance criteria and environmental conditions.

Digital Signal Processing (DSP): DSP techniques are applied to MEMS IMU outputs for signal conditioning and noise reduction. OEMs often work with customers to develop proprietary algorithms for filtering, averaging and processing sensor data in real time. DSP enhances sensor accuracy and stability, particularly in dynamic applications prone to vibration and motion.

Temperature Compensation: MEMS IMUs may incorporate temperature compensation mechanisms to maintain performance across temperature variations. Customers can work with OEMs to use temperature sensors or internal algorithms to dynamically adjust sensor parameters and minimize thermal drift effects based on specific applications.

Bias and Scale Factor Estimation: OEMs perform bias and scale factor estimation to characterize sensor errors. Advanced calibration methods, such as Allan variance analysis or closed-loop calibration, are employed to identify and correct sensor biases and scale factors, ensuring consistent performance throughout the operating lifetime in a customer’s application.

Advantages of Integrating MEMS IMUs from OEMs

Integrating quartz or silicon MEMS IMU technology directly from inertial sensor OEMs like Analog Devices, Seiko Epson, Silicon Sensing or Honeywell offers significant advantages compared to using IMUs from integrators who combine sensors from different manufacturers. The primary advantage lies in the deep knowledge and expertise that sensor manufacturers possess about their own technology, enabling them to optimize sensor performance, identify weaknesses, and exploit specific features for various applications. Here’s a detailed exploration of these advantages:

In-Depth Sensor Knowledge: OEMs have extensive knowledge of their own sensor technologies, including design principles, fabrication techniques, and operational characteristics. This comprehensive understanding allows them to optimize sensor performance, fine-tune sensor parameters, and address specific weaknesses or limitations.

Performance Optimization: OEMs can leverage their expertise to optimize IMU performance for various applications. This includes fine-tuning sensor calibration, implementing advanced signal processing algorithms, and enhancing sensor accuracy, stability and reliability based on real-world usage scenarios. OEMs can adjust sensor parameters and configurations to enhance performance for specific applications. This may involve modifying sensor response curves, bandwidth settings, or filtering techniques to achieve optimal results in challenging environments.

Application-Specific Customization: OEMs can provide tailored solutions and customization options to meet specific application requirements. They can recommend sensor configurations, communication protocols, and integration techniques that align with the intended use case, ensuring optimal performance and compatibility. OEMs possess detailed knowledge of sensor characteristics, including noise levels, bandwidth, drift rates, and environmental sensitivities. This understanding allows them to exploit specific sensor features for optimizing performance in diverse applications.

Advanced Sensor Fusion and Integration:
OEMs often develop sophisticated sensor fusion algorithms and integration techniques that leverage the strengths of their IMUs. This enables seamless customer or end-user integration with other sensors (e.g., GPS, magnetometers) to enhance overall system performance, such as in navigation, motion tracking, and stabilization applications.

Comprehensive Technical Support: OEMs offer comprehensive technical support, documentation, and application notes specific to their IMUs. This support is invaluable for system integrators and developers, providing guidance on sensor setup, troubleshooting, and implementation best practices.

Access to Latest Innovations: OEMs continuously innovate and release new sensor technologies and product updates. Integrating directly from OEMs ensures access to the latest advancements in MEMS IMU technology, enabling developers to stay at the forefront of sensor capabilities and performance.

Supply Chain Stability: Most MEMS inertial sensor OEMs strive to vertically integrate their products as much as possible. In doing so, elaborate measures are taken to ensure continuity of supply not only for the piece parts required for MEMS IMU manufacture, but also for products they sell to their customers.

Conclusion

The debate over the choice between Quartz and Silicon MEMS inertial sensors for high-performance applications remains a critical topic, influenced by the compelling case for integrating IMUs directly from OEMs versus using integrators of other manufacturers’ sensors. This article has elucidated key considerations in this discourse, emphasizing the advantages inherent in OEM-supplied IMUs for optimized performance and reliability.

Engineers and developers targeting high-performance applications benefit from the profound sensor knowledge and domain expertise possessed by inertial sensor OEMs such as Analog Devices, Epson, Silicon Sensing and Honeywell. These OEMs excel in optimizing sensor performance through advanced calibration techniques, parameter adjustments, and digital signal processing tailored to specific application requirements. By leveraging their deep understanding of sensor characteristics, OEMs facilitate the exploitation of sensor features to enhance performance in diverse operational environments. Moreover, the advantages of integrating OEM-supplied MEMS IMUs extend beyond technical capabilities to encompass comprehensive support, application-specific customization, and access to leading-edge innovations. OEMs offer robust technical documentation, application notes, and responsive customer support, empowering engineers to navigate complex integration challenges and optimize sensor performance effectively.

This article underscores the compelling case for engineers and developers seeking high-performance MEMS IMUs to integrate directly from OEMs. By harnessing OEM expertise, engineers can unlock the full potential of quartz or silicon MEMS inertial sensors, achieving superior performance, reliability, and innovation in critical applications across aerospace, defense, robotics, and beyond. The integration of OEM-supplied IMUs represents a strategic imperative for realizing technological excellence and competitive advantage in the rapidly evolving landscape of inertial sensing technologies.

Author

David Gaber has overseen the Inertial Sensors Group at Epson America since 2012 and is responsible for scaling the division’s growth. Prior to joining Epson, David led the applications engineering team at Systron Donner Inertial, supporting quartz MEMS sensor integration on the U.S. Navy’s Mark 48 and 54 torpedoes as well as JDAM and various military aircraft upgrade programs. Previously, David worked as a program manager for U.S. Air Force contracts performed abroad in support of numerous manned and unmanned aircraft initiatives.

References

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[3] Chen, L., & Wang, X. (2019). Review of MEMS Inertial Sensor Technology for Defense Applications. IEEE Transactions on Aerospace and Electronic Systems, 55(2), 689-702.

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[7] Johnson, C., & Martinez, D. (2017). Advances in Quartz MEMS IMUs for Aerospace and Defense. Proceedings of the IEEE, 105(8), 1503-1517.

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The post The Inertialist: Quartz or Silicon? appeared first on Inside GNSS - Global Navigation Satellite Systems Engineering, Policy, and Design.

Alternative. Backup. Complementary. These words describe the global efforts to find technologies capable of fulfilling critical infrastructure requirements for positioning, navigation and timing (PNT) in the absence, degradation or disruption of GNSS services. This search has been ongoing and continues to evolve. Here, we provide a historical look back at some of the efforts in the U.S. and Europe, a snapshot of the current PNT environment and how it has influenced more recent developments in the search for resilient PNT solutions, and a glimpse into what may lie ahead in that quest.

The U.S. Leads the Charge 

For years, the U.S. has been sounding the clarion call to protect, toughen and augment PNT.

The 2021 analysis prepared by the Volpe National Transportation Systems Center under the direction of the U.S. Department of Transportation (DOT) was one of the early studies charged to identify viable backups or complements to GPS. 

The Volpe Report evaluated the effectiveness of 11 different technologies from various companies and organizations based on several performance characteristics (e.g., resilience, accuracy, coverage and deployment feasibility) using 14 Measures of Effectiveness (MoE), across various scenarios. 

Specifically, the five timing scenarios assessed vendor systems based on four attributes: 72-Hour Bench Static Timing, Static Outdoor Timing, Static Indoor Timing, Static Basement Timing, and eLORAN Reference Station Offset. DOT also developed four positioning scenarios to assess vendor systems based on these five attributes: Dynamic Outdoor Positioning with Holds, 3D Positioning, Static Outdoor Positioning, and Static Indoor Positioning.

Volpe, however, also concluded no single alternative technology can fully replace GPS or meet all PNT requirements across its four identified critical infrastructure sectors (Transportation, Telecommunications, Energy and Space Operations). Instead, it recommended the use of a diverse portfolio of complementary technologies to enhance the nation’s critical infrastructure. It also emphasized the importance of continued research and development, the need for public-private partnerships to explore and deploy effective PNT solutions and the necessity of federal guidance and coordination to ensure the interoperability and security of alternative PNT (A-PNT) systems.

Europe Gets into Alt-PNT Game 

It has been three years since the Volpe Report was published, and new technologies have emerged that were not tested. Hence, the European Commission (EC) Joint Research Centre (JRC) in Ispra, Italy, launched its own testing campaign for A-PNT, using a Call for Tender from the Directorate General for Defence Industry and Space (DEFIS). The resultant report presented the findings from this latest and extremely comprehensive European test campaign (“DEFIS Report,” officially titled “Assessing Alternative Positioning, Navigation and Timing Technologies”).

Six companies were awarded EC contracts for the test campaign: OPNT BV, Seven Solutions SL, Satelles Inc., GMV Aerospace and Defence, Locata and NextNav. The JRC used several key performance indicators (KPIs) and related performance characteristics: robustness to interference (including for GNSS frequencies, weak RF, strong RF), encryption-readiness (including for data, signal) and scalability to local, regional or continental areas.

Like the Volpe Report before it, the DEFIS Report does not specify a single “winner” among the technologies tested. Both NextNav and Satelles tech again performed well in several tests. However, studying performance Tables 1 and 2 (as published in the final JRC DEFIS Report), it’s clear Locata’s new technology appears to have been the top performer in this study. Locata was the only technology, amongst all of the PNT candidates, that delivered exemplary performance in all tested environment scenarios, and also across all tested resilience, accuracy, and deployment parameters.

Locata is a terrestrially based technology that offers high-precision positioning and timing. It uses a network of proprietary ground-based transmitters, known as LocataLites, which emit signals that a Locata receiver can use to calculate its position with high accuracy. The Locata network is novel in that its transmitters can maintain sub-nanosecond synchronization without any dependence on GPS, satellites, external corrections, or the atomic clocks relied upon by all other tested systems. This unique new capability was clearly demonstrated during the JRC tests and is documented in the final DEFIS Report. Locata specifically designed this technology to work in areas where GPS and other GNSS signals are unreliable or unavailable.

In the JRC tests, Locata’s tech displayed significant resilience, the ability to maintain operational capability in the face of challenges such as signal interference, jamming or environmental obstacles. Locata tests, conducted in both an industrial test facility in Düsseldorf, Germany, and a “multipath-rich” indoor space at the JRC facility in Ispra, assessed the positioning accuracy of Locata technology against various challenges, including those that affect resilience. The technology’s performance in these diverse environments suggests a high level of resilience, particularly in overcoming signal multipath issues common in urban and indoor environments.

Accuracy, a critical measure for any PNT technology, indicates a system’s ability to provide precise location and timing information. JRC engineers tested Locata systems to measure the precise time transfer capability and positioning accuracy. The tests included a local area component within the JRC facility and a wide area component extending outside the premises, using an outdoor “timing backbone” to also synchronize an indoor positioning network. The specific numerical results of these tests indicate a focus on validating the accuracy of Locata’s technology under different conditions.

The JRC tests also covered the practical aspects of deploying the technology on a wide scale, including infrastructure requirements, scalability and integration with existing systems. For the JRC demonstrations, Locata used its technology at a fully automated port machinery manufacturing and testing facility. The autonomous machinery at the site was used to demonstrate Locata’s centimeter-level performance in environments requiring high precision and reliability, plus its ability to integrate into complex industrial applications. Additionally, the demonstration of UTC time transfer to an indoor Locata Rover suggests the technology’s capability to integrate with global time standards, an important factor for deployment feasibility. The report confirmed that Locata’s ground-based networks provide non-GPS based, centimeter-level positioning accuracy in areas where GPS doesn’t work. 

What did we learn from the Volpe and DEFIS Reports? Despite originating from different regions at different times, they share several commonalities in their findings regarding A-PNT. 

Commonalities and Learnings 

The commonalities of both Volpe and DEFIS reflect a global consensus on the need for resilient PNT solutions that can complement or serve as backups to GNSS. At a high level, both reports also underscore the vulnerabilities of GNSS, including susceptibility to jamming, spoofing and signal degradation in certain environments. This shared concern highlights the critical need for A-PNT solutions to ensure continuity of services for critical infrastructure and national security.

Resilience and accuracy emerged as key performance characteristics in both reports, especially in transportation and telecommunications. Both reports evaluated technologies for their ability to provide reliable and precise PNT information, even in challenging conditions where GNSS signals are compromised. 

From these demonstrations, Locata, NextNav and Satelles seemed to be the top contenders. At the same time, both reports concluded that no single A-PNT technology can fully replace GNSS across all applications and sectors. Instead, they advocated for a diverse portfolio of technologies in a system-of-systems integration to serve different needs and environments in a layered approach. 

The two reports also converged on the needs for further R&D, supportive public-private partnerships and policy frameworks to enhance the resilience of PNT services worldwide. 

With regard to the ongoing need for R&D, they focused on the requirement to enhance the performance, scalability and cost-effectiveness of A-PNT technologies and emphasized the importance of innovation and testing to identify viable solutions that can be deployed at scale. This specific point seems to be at the core of the U.S. Department of Transport Critical National Infrastructure tests. 

Finally, they agreed that on the policy front, considerations for interoperability, standardization and security will ensure these technologies can be effectively implemented within existing infrastructure.

Since the publication of the DEFIS and Volpe Reports, several global events have highlighted the vulnerabilities of relying solely on GNSS and have validated the need for real solutions now.

The Evolving Threat Picture 

In the past few years, the world has witnessed a ramp up in cybersecurity threats, geopolitical tensions, natural disasters, space weather events and climate change as well as technological advancements that come with their own new vulnerabilities. All of these underscore the increasing importance of resilient PNT systems and robust alternative solutions.

Cybersecurity threats, including more sophisticated cyber-attacks on critical infrastructure, have risen in number. Attacks on energy grids, transportation networks and government databases have shown how vulnerabilities in digital and communication networks can be exploited. For example, the energy grid, both in the U.S. and globally, faces numerous virtual (cyber) weak spots that can lead to disruptions in power supply and everyday life unless alternative solutions can shore them up.

Escalating geopolitical tensions involving major powers have led to additional concerns over the security of satellite navigation systems. Instances of GPS signal jamming and spoofing in conflict zones, such as Russia-Ukraine, have extended to nearby regions.

Add to this the increasing frequency and severity of natural disasters, driven by climate change, which pose significant risks to GNSS infrastructure. Hurricanes, wildfires and earthquakes have been known to damage satellite ground stations and other critical infrastructure. A-PNT technologies can ensure continuous operations during and after such events.

Significant space weather events, such as solar flares and geomagnetic storms, have the potential to disrupt satellite operations. If a strong solar flare interferes with satellite communications, this could lead to reduced accuracy or a complete loss of positioning and timing data. This risk underlines the importance of having terrestrial and non-satellite-based systems as viable PNT alternatives.

Finally, technology continues to advance and with it, new vulnerabilities have emerged. The expansion of 5G networks and the Internet of Things (IoT) increases our dependency on precise and reliable timing, predominantly provided today by GNSS. Any disruption in GNSS services could have cascading effects on everything from urban transportation to critical health care services. This interconnectedness highlights the need for diversified PNT solutions to provide independent backup in the event of GNSS failures.

These events collectively illustrate the growing imperative for countries and industries to invest in and develop resilient PNT systems that can ensure continuity and reliability of critical services in the face of diverse and evolving threats. As the need for robust A-PNT solutions has become more critical than ever to safeguard national security, economic stability and public safety, other countries have jumped on the A-PNT bandwagon—notable among these, the United Kingdom (UK).

The UK Launched Its Own Initiative

In response to the growing recognition of the vulnerabilities faced by space-based PNT assets, particularly arising from nearby geopolitical tensions, the UK launched a comprehensive strategy to enhance the resilience and innovation of its PNT services.

Key components of the UK’s PNT strategy included: development of a cross-government crisis plan to ensure immediate short-term preparedness for scenarios where services become unavailable; creation of a National Timing Centre to provide resilient, terrestrial, sovereign and high-quality timing services across the UK; a PNT Growth Policy emphasizing R&D programs, standards and testing activities across various sectors; and a Contextual Complementary PNT (CPNT) Framework to dovetail off work from the JRC and DOT.

In support of this strategy, the UK Research and Innovation Council unveiled a Strategic Priorities Fund. The UK National Timing Centre currently spearheads this 5-year £36 million initiative dedicated to ensuring reliable Time and Frequency services across the UK. It has three main objectives: establish a Resilient Enhanced Time Scale Infrastructure; financial support to the UK industry through Innovate UK; and offering specialized training programs for experts, postgraduates and apprentices.

Specifically, to enhance the nation’s timing resilience, the initiative plans to broaden the network of sites generating time by providing atomic clock backups to ensure users have access to UTC(k) traceable time (think: network of resilient, distributed atomic clocks throughout the UK). This Resilience Enhanced Time Service (RETS) infrastructure includes four sites designed to operate independently of GNSS. 

As the UK continues to ramp up its timing efforts, so too does the USDOT’s effort to develop and implement CPNT technologies.

DOT Ramped Up Its Search

Over the past year, in what can only be characterized as an intensification of effort, the USDOT issued both a Request for Information (RFI) and a subsequent Request for Quotes (RFQ).

The RFI clearly indicated the DOT primarily seeks high Technology Readiness Level (TRL) non-space-based alternatives that can offer accuracy, integrity and resilience under adverse GNSS conditions. It specified stringent requirements for the tech it seeks, including accuracy and integrity in the face of signal disruptions, reliability to withstand a variety of signal threats, and stringent security practices consistent with national cybersecurity frameworks.

In our recent interview with the Office of the Assistant Secretary for Research (DOT/OST-R) Director for the Office of Positioning, Navigation and Timing & Spectrum Management Karen Van Dyke on the follow-on RFQ, she characterized DOT’s effort as “a two-pronged approach” focused on bolstering GPS as well as finding “gap fillers,” to step up if GPS becomes unavailable.

At the Assured PNT Summit Conference in Washington D.C. in late May, Van Dyke announced that the DOT hoped to award contracts to the CPNT candidates selected by the U.S. Government for Critical National Infrastructure testing sometime in June, and they did. 

No One Size Fits All 

One thing is for sure, whether in the U.S., EU or UK, there will be no one size fits all solution for A-PNT | CPNT because the relevant critical infrastructure sectors each have their own specific operational requirements and challenges that make certain A-PNT technologies more suitable than others. What we’ve seen, based on the demonstrations so far, is some tech works for some applications and arguably, some of that tech could work across all.

Together, these technologies could provide the necessary resilience, accuracy and security to support the critical infrastructure sectors identified in the Volpe and DEFIS Reports. In the meantime, all we can do is continue to wait and see what developments will continue to occur both in the U.S. and across the pond, in the search for A-PNT and CPNT solutions that will protect our security, economy and daily lives.

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