The program follows Pulsar-0’s first year in orbit, during which the satellite completed more than 350 transmission passes across four continents and returned 22 terabytes of observation data, with commercial receivers tracking its signals from Finland to Australia.

The inaugural Pulsar Verified cohort includes Trimble, which is bringing devices launched as early as 2018 to Pulsar compatibility, along with Septentrio (part of Hexagon), STMicroelectronics, Safran, StarNav, and Keysight. Septentrio joined Xona’s ecosystem around the time of the company’s Series C fundraise and is working to integrate Pulsar across its next-generation device lineup. Safran’s Skydel and Keysight’s PNT X, both GNSS simulators capable of modeling Pulsar constellation behavior, have separately attained Pulsar Verification, allowing developers to test against the signal before receiver hardware ships. Xona CEO Brian Manning said Pulsar Verified equipment installed in drones, robots, phones, or IoT devices will be ready to use the service as it comes online.

Xona positioned the verification program as a response to escalating jamming and spoofing incidents affecting commercial aviation, shipping, agriculture, and financial systems beyond traditional conflict zones. In live-sky jamming tests, the company said its stronger signal held where GNSS was disrupted, and that Pulsar can shrink a jammer’s effective area by as much as 95%.

The certification push follows a $170 million Series C round closed in March, led by Mohari Ventures Natural Capital with participation from Craft Ventures, ICONIQ, Woven Capital, NGP Capital, Samsung Next, and Hexagon, among others. Xona opened a satellite integration and assembly facility in Burlingame, California, in April to scale production toward a planned 258-satellite constellation, with the first U.S.-built satellites expected to launch later this year. In June, Xona signed a memorandum of understanding with Murata Manufacturing — an existing investor through its Wonderstone Ventures arm — to explore Pulsar integration into communications modules, timing devices, and industrial electronics for data centers, financial networks, and 5G/6G infrastructure.

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The system draws on GNSS for primary high-precision timing, ATSC 3.0 terrestrial broadcast signals — including the Broadcast Positioning System (BPS) — as a GPS-independent complement, and network-based precision time protocols for integration with IP infrastructure.

The company positions the approach as an alternative to conventional holdover mode, in which a device runs on its own internal clock during a GNSS outage and gradually drifts from true time. By continuously cross-referencing GNSS, terrestrial ATSC 3.0/BPS signals and network timing protocols, the SDAC is intended to maintain synchronization through jamming, spoofing or satellite signal loss rather than degrading over an outage.

Madeleine Noland, president of ATSC, said in the announcement that ATSC 3.0 was built to support applications beyond video delivery, including time transfer and positioning through BPS, and called the deployment evidence of broadcasting’s role in resilient national timing infrastructure. Dean Goodman, CEO of All 6G, said the product responds to a longstanding need for a true complement to satellite timing, combining satellite, broadcast, terrestrial and network sources into a single system, and linked the effort to FCC Chairman Brendan Carr’s public emphasis on resilient PNT infrastructure.

All 6G said the SDAC is designed and manufactured in the U.S. under the company’s no-Chinese-chip policy, targeting 5G/6G networks, data centers, power grids, financial systems, defense applications and other critical infrastructure requiring assured PNT. The device is available now for evaluation and deployment.

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For Canada’s Calian, the answer begins with the best possible GNSS reception. Speaking with Inside GNSS at Eurosatory, Goran Jedrejčić, Head of Sales for Europe at Calian Advanced Technologies, described a company that has spent decades building high-performance GNSS antennas and is now applying that expertise to the growing challenge of jamming and spoofing.

Calian employs roughly 5,000 people worldwide and operates across sectors ranging from defense and space to healthcare and nuclear applications. Jedrejčić represents the company’s GNSS division, which traces its roots to Tallysman Wireless. “Tallysman was very well known in high-end applications and high-performance applications,” he said. “That group was taken over by Calian some four years ago, but nothing about our quality has changed.”

The group’s focus is research, development and manufacturing of GNSS antennas and increasingly, smart antennas with integrated receiver technology. “‘Smart’ means the receiver is already deep inside,” Jedrejčić said. The system integrates processing electronics directly within the antenna assembly. “You see a small footprint. There is no extra box you need to place somewhere, no extra cables. This is what’s coming on unmanned platforms.”

Manufacturing, ranging from small antennas to complex anti-jamming antennas, remains concentrated in Canada, something Jedrejčić views as both a quality and supply-chain advantage. He believes technical performance must be matched by dependable manufacturing and logistics. “If you think about it, the supply chain is very important,” he said. “If you’re able to be a reliable supplier and having all our manufacturing in a country like Canada, it means we can ship very fast. That’s a big deal nowadays.

“We focus mostly on L-band, on GNSS, Iridium, that kind of frequency range, and specialized high-end antennas, to deliver the best signal integrity,” he said. “We put a lot of effort into getting the best possible performance, high accuracy for positioning.” And that emphasis has naturally grown to encompass resilience.

Small size, low power, high resilience

“We have fixed radiation pattern antennas [FRPAs] which mitigate everything on the horizon,” Jedrejčić said. “So if there is a horizon-based jammer or spoofer, it will basically ignore that.” Additional protection is provided by filtering technologies designed to reject interference before it reaches the receiver. “It’s called XF+ filtering,” Jedrejčić said, “which again makes your system very, very resilient.”

Another clear differentiator for the company, he said, is the focus on size, weight and power. “What we have that is quite unique is a specialized CRP [controlled reception pattern] antenna which is extremely light, extremely low power consumption while still showing excellent performance.” That combination is increasingly important for unmanned systems operating on limited power budgets. “Our four-element CRPA consumes 0.7-watts of power,” he said. “A comparable conventional antenna is about 15 to 20-something watts, so that’s a really big difference.”

The Calian portfolio is finding applications across a remarkably wide assortment of platforms. “You can see us from water up to space,” he said. “We are in submersible platforms, as well as on the sea surface, in many ships. We are of course on every land platform, and we’re also in satellites.”

As interference incidents continue to draw attention across Northern Europe, one particularly relevant application for Calian customers is maritime navigation in the Baltic region, where resilient PNT capabilities have become an increasingly important operational requirement.

For Jedrejčić, the company’s move into defense-oriented GNSS solutions represents less of a pivot than a natural evolution. “We have been doing high-precision antennas required in geospatial applications since the beginning, in drones doing photogrammetry, for example, where you need that high precision. We started there,” he said, “and over time we have added superior filtering and other resilience solutions.”

The company’s customers have undergone a similar transformation. “Many companies, many drone builders, have gone from civilian to defense,” Jedrejčić said. “We’ve just followed that. We’ve been with them the whole time.”

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The deal combines Aireon’s space-based air traffic surveillance and aviation intelligence services with Iridium’s global satellite communications network and PNT capabilities, giving Iridium a single platform for real-time aircraft visibility, connectivity and operational data for aviation customers worldwide.

“Iridium and Aireon are fully aligned in our mission to advance the future of aviation safety. What began as a bold vision more than a decade ago has become a foundational capability for global air traffic management, delivering real-time surveillance and operational intelligence on a truly global scale,” said Iridium CEO Matt Desch, adding that the companies will keep investing in technology meant to make aviation safer, more efficient and more resilient over the coming decades.

Aireon will continue operating as a wholly owned Iridium subsidiary, with Don Thoma remaining as Aireon’s CEO and reporting to Desch, preserving both leadership continuity and alignment with Iridium’s broader strategy.

The closing lands at a notable moment for Iridium. On June 29, Rocket Lab Corporation (Nasdaq: RKLB) announced a definitive agreement to acquire Iridium outright for $54 per share in cash and stock, in a deal both companies described as merging Rocket Lab’s launch and satellite manufacturing capabilities with Iridium’s global network, L-band spectrum and government partnerships. Desch, in Rocket Lab’s announcement, said the combination would let Iridium accelerate the next generation of IoT, aviation, maritime, PNT and national security capabilities as part of a fully integrated, end-to-end space company. That transaction is separate from and has not yet closed as of the Aireon completion, meaning Iridium finalized the Aireon deal as an independent company even as its own acquisition by Rocket Lab moves through the pipeline.

Aireon’s ADS-B and aviation-surveillance assets, along with Iridium’s PNT and satcom business, are now set to become part of Rocket Lab’s satellite manufacturing and launch platform once that deal closes, rather than remaining under an independent Iridium.

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The core differentiator is TAP, which delivers correction via L-band satellite signal rather than a local base station or cellular network. If RTK correction drops out, the TAPFill function automatically switches to TAP while keeping the positioning result aligned to the RTK coordinate reference frame, preserving guidance continuity. If GNSS signal is lost entirely or quality falls below threshold, the system issues a warning and requires the operator to disengage and manually confirm conditions before resuming.

Core hardware includes the GC30 Guidance Controller, TC120 tablet terminal (10.1″, IP67), TES30 electric steering motor, camera, and vehicle-specific brackets. Tersus says the kit is compatible with over 90% of ag vehicles across brands, with installation recommended through trained personnel or authorized dealers. The system supports all major constellations — GPS, GLONASS, BeiDou (BDS-3), Galileo, QZSS, SBAS, IRNSS — plus the L-band TAP signal.

Notably, Tersus is also pursuing an open-source-oriented integration path with the AgOpenGPS community, separate from its standard commercial licensing — framed by the company as a way to pair its GNSS/INS fusion and motor-control hardware with community-developed flexibility. ISOBUS VT&TC compatibility and section control for sprayers/seed drills are in development, alongside a 12-inch tablet option. Indicative retail pricing runs roughly $4,000–$8,000, dealer/region/config dependent.

Mark Chen, Tersus’s Director of Digital Media, positioned the AG993 as a stepping stone toward broader autonomy — pointing to ISOBUS Tractor Implement Management, multi-sensor fusion (cameras, LiDAR, radar, IMU) for obstacle detection, and data connectivity with platforms like John Deere Operations Center and agrirouter as the next layers, alongside growing European regulatory/cybersecurity requirements around geofencing and human-machine responsibility boundaries.

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These events can now be visualized within a day or two of occurrence at websites that use ADS-B transmissions to infer the locations and types of jamming and spoofing, such as [2]. Real-time detection, mitigation and avoidance of these events is now one of the most active areas of GNSS research.

Users with the most demanding accuracy and integrity requirements, such as civil aviation, typically rely on differential corrections and integrity information provided by services such as Satellite and Ground-based Augmentation Systems (SBAS and GBAS, respectively). Corruption of the transmissions providing this information (“message spoofing”) is another means of generating misleading information (large, unbounded errors) and is a particularly concerning threat, as it can be done using a single PRN and need not overpower any existing signals. Further, it can introduce a bias on the position without affecting the GNSS-derived velocity or acceleration, making comparisons against other sensors for these elements ineffective.

The best way to prevent malicious alternation of GNSS corrections is to provide a means to authenticate the information in these messages so users can be assured the received data comes from the intended source. A simple message authentication protocol is included in the GBAS VHF Data Broadcast (VDB) between ground systems and users [3] but is limited to indicating which message slots should contain information from a given ground station. A more advanced cryptographic authentication technique is being developed for SBAS that is backward-compatible with legacy signals and should prevent any receiver from accepting SBAS information from anyone aside from the actual SBAS provider [4,5], but the work needed to standardize and implement it is expected to take several more years. 

To provide some level of SBAS message spoofing mitigation before cryptographic authentication is available, simple methods have been proposed in [1] to limit the magnitude of errors that could be generated by message spoofing. This column explains one of these methods, the background behind it, and its projected effectiveness in limiting worst-case errors from SBAS spoofing.

SBAS Correction Magnitudes and Spoofing Potential

When GBAS and SBAS were first conceived, GPS implemented a deliberate range-domain degradation called Selective Availability (SA). To counter the effects of SA, SBAS correction limits were made quite large: more than 250 m for clock errors and over 128 m in each of three orbital axes. However, in 2001, GPS eliminated SA and has subsequently committed to maintain significantly smaller errors [6]. But the L1 SBAS and GBAS standards were set prior to SA’s removal, and the potential to introduce large errors through erroneous corrections remains a part of the legacy L1 standards.

SBAS corrections can be used to create pseudorange errors that are up to about 160 m on L5 [7] or over 600 m on L1 [8]. L5 corrections only contain satellite clock and orbit values that are limited to ~64 m on adjustments to the clock and the three cartesian orbital coordinates. Cartesian (XYZ) orbital adjustments can be mapped into radial, along-track, and cross-track (RAX) adjustments whose upper values are dependent on satellite location. At least 97% of the radial error maps into user pseudorange error, while no more than 24% of the along-track and cross-track errors map into user pseudorange error. L1 corrections are larger, as they were designed to handle selective availability and ionospheric corrections. Fast Correction (FC) clock corrections can be as large as 256 m, while Long-Term Corrections (LTC) include orbital XYZ terms that can reach 128 m along with a clock term that can be as large as 143 m. Depending on satellite location and elevation angle, the projected pseudorange errors can range from 530 m to 675 m if using only FCs and LTCs.

In addition, the SBAS rate correction terms could make these correction errors more than an order of magnitude larger by making the time of applicability hours in the past. This undesirable property was recently recognized, and the SBAS Minimum Operational Performance Standards (MOPS) [7,8] are being changed to have the receiver limit the time period over which the rate terms could apply. Rather than potentially creating kilometers of error, they will be limited to roughly half the magnitude of the above correction terms. Altogether, the pseudorange errors from the satellite clock and orbit correction and correction rates can be of the order of 250 m on L5 and 650 m on L1.

An SBAS spoofer would also have control over which satellites the receiver uses and what their confidence values are, so they could create geometries with worse properties than commonly experienced. Typically, pseudorange error will be multiplied by a value less than three when mapped into position error. However, the spoofer can significantly increase this factor by controlling which satellites are used in the position solution and how much weight is assigned to each. 

Figure 1 shows the results of a GPS satellite geometry simulation using the default 24 satellite constellation [6] and users located around North America over 24 hours. The spoofer can control the magnitude and sign of each satellite measurement as well as maximize the projection along any position axis. By maximizing the error magnitudes for each satellite and the sum of the absolute values of the projection matrix (S) elements corresponding to a particular direction, the spoofer would maximize the error it can create along that direction [1]. For each user location and time step, every subset geometry that could support a 50 m Vertical Alert Limit (VAL) and 40 m Horizontal Alert Limit (HAL) were evaluated. This simulation can choose User Differential Range Errors (UDREs) and Grid Ionospheric Vertical Errors (GIVEs) for L1 or Dual Frequency Range Errors (DFREs) for L5. Low values for these parameters allow the alert limits to be made quite small for geometries ordinarily not available for use. 

Figure 1 shows histograms of the sum of the absolute value of the vertical-axis (Up) projection matrix values across all satellites in view for L1 users (left) and L5 users (right) (the histograms for East and North directions look nearly identical). Note that pseudorange errors could be multiplied by factors of order 10 to 50 for L1 or from 5 to 25 for L5 in the position domain depending on the underlying GPS satellite geometry. This means a spoofer could create position errors as large as 32 km for L1 and up to 6 km for L5. This clearly shows the need for some level of mitigation of SBAS message spoofing.

Correction Magnitude Limits and GNSS Commitments 

SBAS and GBAS messages include corrections for errors highly correlated between reference stations and users that are the primary means of improving accuracy beyond uncorrected (“standalone”) GNSS. The corrections computed by SBAS and GBAS must be checked in real time to confirm they fall within the limits of their message fields (i.e., the largest values that can be accommodated). To avoid failing this check, these message fields were designed to allow for correction magnitudes as large as could be envisioned during early system design in the early-to-mid 1990s. However, during subsequent development, it was realized that setting tighter limits helped detect and exclude system anomalies that were difficult to detect otherwise. For example, tighter limits on pseudorange correction and correction rate message parameters were shown in [9] to detect certain types of ephemeris anomalies arising from unannounced satellite maneuvers that are difficult to detect with other monitors.

In the last few years, each GNSS Constellation Service Provider (CSP) has made certain commitments about their constellation performance to enable their use by the aviation community [6,10,11,13]. Table 1 contains the commitments for four core constellations: GPS, GLONASS, Galileo and BeiDou (BDS). The most relevant parameters are σ_URA, a zero mean Gaussian overbound of nominal signal in space ranging errors; P_sat, the probability that a satellite has a fault, defined here as an error not overbounded by σ_URA independently of all other satellites; P_const, the probability that a single fault will affect more than one satellite within the constellation; and MFD, the mean fault duration.

GPS satellites broadcast their own σ_URA values, which can change over time, particularly if the satellite ephemeris has not been refreshed for many hours. It is most often set to 2.4 m. Figure 2 shows a histogram of the frequency of occurrence of the broadcast URA values from 2008 through 2025. A value of 2.4 meters was sent 91.8% of the time, while a value larger than 4.85 m was sent slightly more than 0.1% of the time. Note that GPS has set P_const to be 10^-8 or less. Thus, it is extremely unlikely GPS will have two or more faulty satellites at any given time. The definition of a fault for GPS is that the satellite clock and ephemeris errors together project to an error greater than 4.42 times σ_URA for any user. This corresponds to a 10.6 m upper limit most of the time (when σ_URA is 2.4 m). Unfortunately, none of the other constellations have made such a strong commitment.

Observed Constellation Performance

The left side of Figure 3 shows observed GPS constellation performance from 2008 through 2025. It shows the maximum projected clock and ephemeris errors for the satellite with the largest absolute errors at each time epoch in blue and the satellite with the second largest concurrent error in red. On June 17, 2012, the maximum error grew to 448 m, which is off the top of the plot. All other maximum projected errors over this period have been below 50 m. The second largest concurrent error observed in that time frame was 5.64 m. Note that in early 2024, GPS operational changes significantly improved its overall accuracy. 

The right side of Figure 3 shows the same data normalized (divided) by the broadcast value of σ_URA. Only rarely are the blue values greater than 4.42, which is the value that, when exceeded, is declared a GPS fault. All data is shown except for the June 17, 2012, fault, which corresponded to 187 times σ_URA. These instances correspond to the nine fault events that have occurred over this 18-year period. No simultaneous faults have been observed, confirming the extreme rarity of simultaneous faults, and the number of independent faults is well below the expected number corresponding to the GPS commitment for P_sat in Table 1 (10^-5).

Figure 4 shows the same results for Galileo. The left side of Figure 4 shows observed Galileo constellation performance from 2020 through 2025. It shows the largest and second largest projected errors in blue and red, respectively. There were five errors over this period that were larger than 18 m. They occurred on January 21, 2021; September 5, 2021; April 29, 2022; August 31, 2022; and July 21, 2024. All other projected errors have been below 18 m. The second largest concurrent error observed in that time frame was 1.85 m.

The right side of Figure 3 shows the same data normalized (divided) by the broadcast value of σ_URA. Only rarely are the blue values greater than 4.42, which is the value that, when exceeded, is declared a GPS fault. All data is shown except for the June 17, 2012, fault, which corresponded to 187 times σ_URA. These instances correspond to the nine fault events that have occurred over this 18-year period. No simultaneous faults have been observed, confirming the extreme rarity of simultaneous faults, and the number of independent faults is well below the expected number corresponding to the GPS commitment for P_sat in Table 1 (10^-5).

Figure 4 shows the same results for Galileo. The left side of Figure 4 shows observed Galileo constellation performance from 2020 through 2025. It shows the largest and second largest projected errors in blue and red, respectively. There were five errors over this period that were larger than 18 m. They occurred on January 21, 2021; September 5, 2021; April 29, 2022; August 31, 2022; and July 21, 2024. All other projected errors have been below 18 m. The second largest concurrent error observed in that time frame was 1.85 m. 

The right side of side of Figure 4 shows the same data but now divided by the fixed Galileo σ_URA value of 6 meters from Table 1. The largest fault occurred in September 2021 and corresponded to a 540 m fault, or 90 times σ_URA. There were five fault events observed in this five-year period. No simultaneous faults have been observed, and the number of independent faults is well below the expected number corresponding to the committed value of P_sat.

SBAS Correction Limitation Algorithm

These results show that both GPS and Galileo meet their respective performance commitments with margin. Based on this, [1] proposes monitoring for large SBAS corrections on multiple GPS satellites to serve as an indication of a potentially spoofed signal. In the inequality in Equation 1, the projected clock and ephemeris correction for satellite j to the user receiver is labeled as ∆y_j. A common SBAS time offset component is removed by differencing each projected correction with the median value from all such projected corrections. The median is chosen as it is robust to a small number of outliers. This difference is compared against the expected uncertainty in the GPS error magnitude according to σ_URA and the uncertainty in the SBAS correction accuracy according to σ_UDRE. For dual frequency evaluations σ_UDRE is replaced by σ_DFRE.

Because σ_URA and σ_UDRE represent conservative overbounds on the expected errors, it is exceedingly rare for 4.42 multiplied by either term to fail to bound their respective errors. Therefore, it is unlikely that more than one GPS satellite exceeds the inequality in Equation 1 at any given time (indeed, it will be very uncommon for even one to do so). Thus, if two or more projected GPS corrections exceed this threshold, the user should deselect this SBAS signal and use a different one or, if another SBAS is unavailable, conclude that SBAS corrections can no longer be trusted. 

When σ_URA and σ_UDRE are small, this constraint places much tighter limits on the correction magnitudes than the existing message structure allows. Assuming the GPS signals are genuine, Figure 2 shows that the GPS σ_URA is below 4.85 m nearly 99.9% of the time. The σ_UDRE can be much larger, but if it is made larger than 4.6 m, it cannot be used for vertical guidance per requirement [R229-227] of [8]. Further, increases in σ_UDRE will be reflected in increased protection levels and decreased availability. Therefore, Equation 1 effectively limits the correction error magnitude to 

This approach still leaves one satellite vulnerable to the possibility of a much larger spoofing error. This motivates a further condition: if a GPS satellite has a correction value that satisfies Equation 1, and its correction magnitude is greater than 30 m, that GPS satellite should be excluded from the SBAS position solution. This additional constraint can be expressed as:

Based on the data in Figure 3, there have only been four events in the last 18 years where a GPS satellite could have met the conditions of Equations 1 and 2 and was then excluded. It is very likely that the affected satellite would have also been set unusable by SBAS during these events due to the sudden large changes in the clock or orbital behavior. Thus, excluding a GPS satellite based on Equations 1 and 2 would not have any noticeable effect on availability.

Given a 30 m upper bound on GPS correction error, this method would place an upper limit on the position error due to erroneous corrections caused by spoofing ranging from roughly 300 to 1,500 m for L1 and 150 to 750 m for L5. A limitation of this approach is that it does not address the risk erroneous ionospheric corrections may pose for the L1 service nor the risk erroneous Galileo corrections may pose for the L5 service. Further, the spoofer may still introduce arbitrarily large errors if it exploits GEO/SBAS satellite ranging. Still, the algorithm is very simple and does usefully limit the potential impact of SBAS spoofing despite not providing complete protection.

Observed SBAS Behavior

This section examines the observed behavior of the existing SBAS services to ensure the risk of false alarms (when spoofing is not present) would be sufficiently low. The left side of Figure 5 shows the largest (blue) and second largest (red) normalized projected corrections for WAAS on a typical day (May 31, 2025). The right side of Figure 5 shows the second largest normalized projected corrections for other SBAS (EGNOS, MSAS, GAGAN, KASS and SouthPAN). The plotted data is described by the ratio of the left and right-hand sides of the inequality in Equation 1 without the 4.42 multiplier. These values are across all possible users that can see a given satellite above 5°, whether the user is within the visibility footprint of the SBAS GEO satellite or not. Further, the two data points for the same time step in the left plot are not necessarily at the same location (i.e., the user location that sees the maximum second largest value likely sees a smaller largest value).

In the left-hand plot in Figure 5, both the largest and the second largest terms are well below the suggested threshold of 4.42. The second largest value is below 1.3 for WAAS. In the right-hand plot, GAGAN’s second largest value was just above 2.0, while the others are all below 1.5. 

Other days, including the rare days with GPS faults, have been examined and show very similar upper limits on the observed second largest normalized projected error. The possibility of false alarms from unnecessarily large SBAS corrections appears to be very small, with all SBAS having values less than half of the 4.42 threshold required to violate the inequality in Equation 1. Note that, for the purposes of this monitor, there is nothing sacrosanct about the 4.42 multiplier in Equation 1 or the constellation commitments shown in Table 1. Taken together, Figures 3, 4 and 5 suggest the commitments for GPS and Galileo are conservative, as expected. Therefore, while these commitments should be the basis of an algorithm standardized in the SBAS MOPS, a multiplier significantly smaller than 4.42 could be used by receiver manufacturers to further limit the magnitude of undetected SBAS spoofing errors.

Position Domain Algorithm Using ARAIM

This simple correction-domain monitor algorithm seeks to avoid the user receiver calculating two separate position solutions, as doing so had been identified as computationally undesirable. However, should the receiver have the capability to calculate both SBAS and RAIM/ARAIM solutions at once, a direct comparison between the two can be very effective. RAIM/ARAIM (based on standalone GNSS without differential corrections [12]) is suggested as the basis for comparison because it also produces a trusted position estimate and associated protection levels. 

A detailed algorithm using ARAIM is defined in [1]. Results show it produces lower limits on undetected SBAS message spoofing errors than the correction-domain algorithm, particularly if dual-frequency ARAIM is applied. 

Conclusion

This article reviews the key results in [1] regarding simple techniques to detect and limit the potential errors caused by SBAS message spoofing. The correction-domain monitor proposed is very simple and can be easily added to existing user receivers with a very low likelihood of false alerts. The ARAIM-based position-domain monitor proposed in more detail in [1] further limits the potential errors but requires significantly more calculations in user receivers. While imperfect, one or both of these monitors should be implemented in current receivers to mitigate SBAS message spoofing risk prior to the introduction of cryptographic authentication in SBAS in the coming years. 

Acknowledgements

The authors gratefully acknowledge the support by the U.S. Federal Aviation Administration (FAA) for this work under MOA 693KA8-22-N-00015.

References 

(1) T. Walter, et al., “Limiting the Potential Impact of SBAS Spoofing,” Proc. ION Pacific PNT 2026, Honolulu, HI, April 2026. http://web.stanford.edu/group/scpnt/gpslab/pubs/papers/Walter_ION_PPNT_2026_Limiting_SBAS_Spoofing.pdf.

(2) “GNSS Interference Detection Using ADS-B” (website). https://rfi.stanford.edu/.

(3) GNSS-Based Precision Approach Local Area Augmentation System (LAAS) Signal-in-Space Interface Control Document (ICD), RTCA SC-159, DO-246E, July 2017.

(4) J. Dennis, et al. (2024). “SBAS Authentication Standards,” Proc. ION GPS/GNSS 2024, Baltimore, MD, Sept. 2024. http://web.stanford.edu/group/scpnt/gpslab/pubs/papers/Dennis_ION_GNSS_2024_SBAS_Authentication_Standards.pdf.

(5) J. Anderson, Designing Cryptography Systems for GNSS Data and Ranging Authentication, Ph.D. Dissertation, Stanford University, Dec. 2024. http://web.stanford.edu/group/scpnt/gpslab/pubs/theses/JasonAndersonThesis2024.pdf.

(6) Global Positioning System Standard Positioning Service Performance Standard. U.S. Dept. of Defense, 5th Ed 2020. https://www.gps.gov/sites/default/files/2025-07/2020-SPS-performance-standard.pdf.

(7) Minimum Operational Performance Standard for Galileo/Global Positioning System / Satellite-Based Augmentation System Airborne Equipment. EUROCAE WG-62, ED-259A, June 2023.

(8) Minimum Operational Performance Standards (MOPS) for Global Positioning System/Satellite-Based Augmentation System Airborne Equipment. RTCA SC-159, DO-229F, June 2020.

(9) H. Tang, et al., “Ephemeris Type A Fault Analysis and Mitigation for LAAS,” Proc. IEEE/ION PLANS 2012. Indian Wells, CA, April 2010. http://web.stanford.edu/group/scpnt/gpslab/pubs/papers/Tang_IEEEIONPLANS_2010_EphemerisTypeAFaultMitigationforLAAS.pdf.

(10) Galileo Open Service—Service Definition Document (OS SDD) (Issue 1.3). European GNSS Service Centre, Nov. 2023. https://www.gsc-europa.eu/sites/default/files/sites/all/files/Galileo-OS-SDD_v1.3.pdf.

(11) ICAO Standards and Recommended Practices, Annex 10—Aeronautical Communications, Vol. 1. International Civil Aviation Organization, 8th Ed., July 2023.

(12) J. Blanch, et al., “Baseline Advanced RAIM User Algorithm: Proposed Updates,” Proc. ION ITM 2022, Long Beach, CA, Jan. 2022. http://web.stanford.edu/group/scpnt/gpslab/pubs/papers/blanch_ION_ITM_2022_ARAIM.pdf.

(13) J. Dennis, et al., “Draft Vertical ARAIM Standards,” International Civil Aviation Organization, Navigation Systems Panel (NSP) JWGs/12, WP 12, May 2024.

Authors

Todd Walter received his Ph.D. in applied physics from Stanford University in 1993. He is a research professor in the Department of Aeronautics and Astronautics at Stanford University. His research focuses on implementing high-integrity air navigation systems. He has received the ION Thurlow and Kepler awards. He is also a fellow of ION and has served as its president. 

Rebecca Wang is a graduate student in the GPS Research Laboratory working under the guidance of Professor Todd Walter in the Department of Aeronautics and Astronautics at Stanford University. Prior to joining the lab, Rebecca received her B.S. in Aerospace Engineering at the University of Texas at Austin. Her research interests include multi-GNSS integrity for aviation and high-accuracy navigation.

 Juan Blanch is a senior research engineer at Stanford University, where he works on integrity algorithms for Satellite-based Augmentation Systems and on Receiver Autonomous Integrity Monitoring. A graduate of Ecole Polytechnique in France, he holds an MS in Electrical Engineering and a Ph.D. in Aeronautics and Astronautics from Stanford University. He received the 2004 ION Parkinson Award for his Ph.D. dissertation and the 2010 ION Early Achievement Award.

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CMFF, established as an Army program of record in April 2025 under the Program Executive Office Command, Control, Communications, and Network, is designed to converge multiple legacy stovepipe systems into a single chassis inside ground and aviation platforms. The chassis integrates capabilities including Assured PNT, tactical communications waveforms, command and control, and force protection electronic attack systems through plug-in cards that can be swapped based on mission requirements. 

In September 2025, the Army selected General Dynamics Mission Systems and Pacific Defense as the two lead developers for CMFF prototype systems. Pacific Defense’s lane is the APNT plug-in card. The Block 2 APNT PIC is a rugged 3U VPX card aligned to the Sensor Open Systems Architecture and CMOSS, fusing data from GPS, alternative navigation signals, inertial sensors, and platform vehicle data to maintain position and timing awareness in contested and GPS-degraded environments. It builds on a Block 1 predecessor developed through prior Army contracts and internal investment.

Under the multi-phase, multi-year program, Pacific Defense will design, build, and test prototype quantities to support Army system integration and test activities. While the initial focus is mounted ground and aviation platforms, the company describes the solution as applicable across airborne, ground, and maritime systems. Primary work will be conducted at facilities in Cedar Rapids, Iowa; Mukilteo, Washington; Sunnyvale, California; and El Segundo, California.

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The deal carries significant implications for the alternative PNT sector. Iridium’s globally harmonized L-band spectrum and low Earth orbit (LEO) satellite network provide what the companies describe as a resilient PNT architecture for applications where GPS and other GNSS are degraded or unavailable. The combined entity will be positioned to accelerate development of Iridium’s next-generation constellation, including direct-to-device services targeted at U.S. national security and emergency response use cases in denied and degraded environments.

Iridium currently supports more than 2.55 million active subscribers across government, defense, aviation, maritime, and commercial markets, and generated $871.7 million in revenue in 2025 with a 57% OEBITDA margin.

“Iridium has built the gold standard in secure, safety critical global satellite connectivity,” said Sir Peter Beck, founder and CEO of Rocket Lab. “By marrying Iridium’s deep heritage, trusted infrastructure, and highly sought-after spectrum with Rocket Lab’s extensive and proven launch and manufacturing capabilities, we have the capability to unlock entirely new markets.”

Iridium CEO Matt Desch cited the convergence of space and terrestrial communications as driving the rationale: “Success will come from those who can bring new innovations to space quickly and sustain them over time as efficiently as possible.”

The transaction, unanimously approved by both boards, is expected to close in mid-2027, subject to stockholder approval and regulatory clearances. Rocket Lab has secured a $3.6 billion senior secured bridge term loan facility from Deutsche Bank and Wells Fargo to fund the cash component.

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The antenna delivers peak gain of up to 1.5 dBi, approximately 50% efficiency across both bands, and an axial ratio of around 4 dB, with stable right-hand circular polarization. It supports GPS, Galileo, GLONASS and BeiDou. The passive variant uses a pin-mount configuration optimized for a standard 70 mm x 70 mm ground plane. The active AGVLB208.A ships with 1.13 mm micro-coax cable and an I-PEX MHF I connector.

Target applications include UAVs, autonomous delivery robots, precision agriculture, telematics and fleet tracking. Taoglas says dual-band operation reduces multipath interference for more reliable centimeter-level positioning in complex RF environments.

An active SMD variant with integrated electronics designed for high-volume automated manufacturing is planned for later this year. The GVLB208 series is available now through Taoglas and its authorized distributors.

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PlanetiQ already provides NASA with ionospheric scintillation data, ionospheric total electron content measurements, and high-SNR GNSS radio occultation data under the program.

The expanded offering gives government researchers access to observations designed to improve understanding of precipitation processes, atmospheric structure, and Earth system dynamics. Polarimetric radio occultation extends traditional GNSS-RO by using dual-polarization receivers — capturing both horizontally and vertically polarized returns from circularly polarized GNSS signals. Because raindrops and snowflakes tend to flatten as they fall, the horizontally polarized component is slightly delayed relative to the vertical; measuring that phase difference yields information about rain and snowfall structure, melting layers, horizontal precipitation banding, and storm intensity variation.

PlanetiQ’s high-SNR receivers are central to the capability’s value for precipitation applications, where greater sensitivity to lighter precipitation and certain cloud structures is critical.

“As more researchers gain access to high-SNR PRO data, we expect both the scientific understanding and the potential operational uses of the technology for precipitation and severe weather monitoring to expand,” said Dr. E. Robert Kursinski, Chief Scientist of PlanetiQ.

Access through the CSDA program is available to NASA researchers, other U.S. government agencies, and international collaborators. PlanetiQ, founded in 2015 and based in Golden, Colorado, received NOAA’s largest-ever commercial satellite weather data contract in 2025, valued at $24.3 million, and holds a $15 million U.S. Air Force STRATFI contract for next-generation weather data from space.

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