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.

The post Tersus GNSS Launches AG993 Modular Autosteer Kit With Built-In Satellite Correction Fallback appeared first on Inside GNSS - Global Navigation Satellite Systems Engineering, Policy, and Design.

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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Announced June 17, Kestrel integrates Honeywell’s HG3900 MEMS Inertial Measurement Unit with an M-code receiver and a multi-GNSS receiver in a package the company says is 40 percent smaller and lighter than comparable EGI products on the market. The M-code capability provides access to the military GPS signal’s enhanced anti-spoofing and anti-jam protections, while the multi-GNSS receiver broadens the available constellation coverage under nominal conditions. When external signals are unavailable, the INS layer maintains self-contained navigation continuity.

The system is intended primarily for Group 2 and 3 collaborative combat aircraft and loitering munitions, where the combination of SWaP-C constraints and GNSS-denial risk is most acute, though Honeywell notes applicability to crewed platforms with similar constraints. The company claims up to 80 percent improvement in navigation accuracy over legacy systems and cost reductions of up to 50 percent — both figures are company-sourced. Kestrel will be available in non-ITAR configurations for international defense and commercial operators.

“This system helps operators maintain mission objectives in environments where legacy GPS systems are lagging behind,” said Matt Picchetti, vice president and general manager of Navigation & Sensors at Honeywell Aerospace. Honeywell has produced more than 60,000 EGI units since pioneering the technology in the mid-1990s.

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For Inertial Labs, the Virginia-based inertial navigation specialist acquired by VIAVI Solutions in 2025, that challenge has become the central driver of product development.

Speaking to Inside GNSS in Paris, Inertial Labs Sales Engineer Jackson Williams said his company has spent more than two decades refining inertial technologies while steadily expanding into sensor fusion and assured navigation. “We’re kind of a 25-year overnight success,” he quipped. The company started in 2001, based in Northern Virginia. “We also have manufacturing in Rapid City, South Dakota, and another R&D office in Kiev, Ukraine,” Williams said.

Over the past two decades, the company has evolved from a sensor manufacturer into a provider of complete navigation solutions. At the heart of that portfolio are gyroscopes and accelerometers, the foundational sensors that measure rotational and linear motion. Those are integrated into inertial measurement units (IMUs), which then form the basis of increasingly sophisticated inertial navigation systems.

Core competence

Williams summarized the company’s mission simply: “We do GPS&I, that is GPS plus inertial navigation, for autonomous vehicles. Starting with the base level sensors, we build our IMUs, and then create more complex inertial navigation systems out of those.” That focus has naturally led the company toward sensor fusion, using further data sources to constrain drift and improve overall navigation performance.

“Our main selling point and our kind of specialty is sensor fusion,” Williams said. “So we bring in aiding forms of data, such as air data computers, magnetometers for heading, fiber optic and man-time use, and low Earth constellation satellites for assured position and navigation and timing.”

Multiple aiding sources help constrain inertial drift and improve solution integrity. By fusing diverse, independent measurements, Inertial Labs seeks to maintain navigation performance in degraded environments, a sensor-diversity approach that Williams described as central to the company’s strategy.

“We bring in things like radio as well, line of sight, time of flight, time of arrival data,” he said. “We fuse these all together, curate them to our customers’ requirements, specifications, and support them when they’re on. We like to be very hands-on with our projects.”

Where it matters

Electronic warfare systems deployed particularly in Ukraine have demonstrated how vulnerable GNSS signals can be to interference. Modern assured-PNT architectures increasingly depend on multiple complementary sensors working together.

One example of a key aiding source is Inertial Labs’ miniature Air Data Computer (ADC). Designed for low size, weight and power consumption, the ADC provides airspeed, altitude and atmospheric measurements that can be fused with inertial data. For unmanned aircraft operating in dynamic flight conditions, those measurements provide an additional reference that helps maintain navigation accuracy during GNSS degradation or loss.

The war in Ukraine has also had a direct influence on product development. Inertial Labs’ Kiev office, originally established in 2006 as a conventional R&D center, now plays an important role in testing and validation. The value of that operational feedback has been significant. “All of our products are battlefield tested and qualified, vetted through our people in Ukraine,” he said. “And with everything that’s going on there, we’re getting a lot of feedback. That’s been a large factor in driving our innovation and our improvements in our devices.”

For many of the companies we met at Eurosatory, the war in Ukraine has become an unprecedented laboratory for navigation technologies. GNSS denial, electronic attack and contested electromagnetic environments have shifted inertial navigation from a backup capability to a central component of military positioning architectures.

Partnering in space

The emphasis on multiple, complementary navigation sources is also reflected in Inertial Labs’ work with the Iridium company. Iridium operates a global low-Earth-orbit (LEO) satellite constellation whose signals are increasingly being explored for resilient PNT applications. LEO-PNT satellites operating in low Earth orbit transmit significantly stronger signals than traditional medium-Earth-orbit GNSS constellations. Inertial Labs’ partnership with Iridium emerged publicly in 2026 with the introduction of IRINS, a system that combines Inertial Labs’ tactical-grade inertial sensors with Iridium’s LEO satellite capabilities.

Despite defense dominating current demand, Williams emphasized that commercial applications remain important. “Right now our main market obviously is the defense space and things of that nature,” he said. “But our IMUs are industrial grade up to tactical grade, so there is a portfolio, or a space in the portfolio for your commercial base use cases.”

He pointed specifically to the company’s LiDAR payload business. “That payload is called RESEPI and is used primarily in the commercial space, meaning farming, construction, things of that nature,” Williams said. Whatever the application, whether it’s about supporting battlefield autonomy, or infrastructure mapping and precision agriculture, the underlying requirement remains the same: reliable motion sensing and navigation in challenging environments.

Eurosatory 2026 showed clearly what our readers already knew – assured PNT is now a necessity rather than a specialized capability. Listening to Williams, a consistent case emerged: the future of navigation will not depend on a single sensor, signal or satellite constellation, but will require the ability to combine and interweave the widest available selection of them.

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SparkPNT’s initial lineup includes four product families. Facet FP is an IP67-rated modular GNSS receiver line available in seven configurations, built for serviceability and long-term upgradeability. TX2 is a quadband GNSS receiver supporting RTK and Galileo HAS for centimeter-level positioning, aimed at surveying applications, with an IP67 enclosure and integrated antenna. The SXM-E Reference Station is a continuously operating reference station with a web-based control interface capable of acting as an NTRIP caster. SXT and SXT-D GNSSDO units are timing products designed to deliver sub-1ns accuracy with enhanced frequency stability.

The company is positioning the line around open-source and customizable architecture rather than the proprietary ecosystems that have historically dominated high-precision positioning and surveying.

“For over twenty years, SparkFun has made cutting-edge electronics more accessible. With SparkPNT, we are applying that exact same philosophy to precision positioning,” said Glenn Samala, CEO of SparkFun Electronics. “We aren’t just launching a new line of GNSS products, we are launching an adaptable, future-proof PNT platform that gives industrial, logistics, robotic, and agricultural sectors commercial-grade precision at a fraction of standard costs—fully backed by a mature manufacturing powerhouse that knows how to deliver at scale.”

SparkPNT founder Nathan Seidle said the company’s goal is to open up a market segment built on closed systems. “For decades, the high-precision positioning and surveying markets have been dominated by proprietary ecosystems. Our goal is to provide field-ready high-precision systems that utilize an open-source and customizable architecture, putting true ownership in the hands of the user.”

SparkPNT is based in Boulder, Colorado.

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According to a Telegram post by Ukrainian Defense Ministry advisor Serhii “Flash” Beskrestnov on June 16, Guarantor was developed by the company Rossiysky Kupol LLC based in Simferopol, Crimea and first appeared in 2024 near Kharkiv—where at least one system was destroyed.

But recently in 2026, Russia began multiplying Guarantor deployment along the southern highway “land bridge” between Russian soil and Crimea to counter Ukraine’s destructive medium-range strike drones that have ravaged fuel truck logistics, causing a stark fuel shortage in Crimea.

In response, Ukraine’s military has released videos showing two strikes on individual trailers of Guarantor systems by the 422nd “Luftwaffe” Unmanned Systems Regiment—attached to the 17th Corps operating in central-southern Ukraine.

Beskrestnov describes an approach intended to interfere with a Starlink satellite’s reception of terminal uplinks by transmitting interference in the relevant Ku-band uplink channels:

“Technically, a Starlink satellite receives signals from terminals in the 14–14.5 GHz range. This range is divided into 8 channels, each 62.5 MHz wide. The Russians basically took 8 satellite dishes, pointed them at the satellite, and each dish transmits interference on its own channel.” Beskrestnov claims this can effectively “deafen” the satellite to terminals in the affected area.

He further details that each Guarantor system encompasses six trailers, each with capacity for two of the system’s eight rotating dish antennas, each of which is covered by egg-shaped domes. Implicitly, then, some trailers carry just one antenna. The antennas can be optionally dismounted, and the power-hungry system can either be sustained by trailer-mounted generators or from external sources.

Beskrestnov concludes each system can effectively deny Starlink access across “roughly 20 square kilometers.” Calculating backwards, this implies a circular radius of just over 2.52 kilometers, or 1.57 miles.

That suggests point defense of a local area, but the radius remains small enough that a Starlink-controlled drone with automatic target tracking could still acquire an optical lock from outside this defensive bubble on targets within the protected area, including Guarantor systems themselves. Indeed, optical lock-on seems possibly present in at least one of the videos released by the 422nd Regiment.

Russian Telegram drone blogger “Unmanned Brotherhood” claims Guarantor is causing Ukrainian forces to complain of “significant problems” but concedes the system has downsides: “the EW system is currently quite large and conspicuous, though this issue is expected to be rectified in the future.” Another Russian technical specialist, Sergei Trukhachev, told Russia’s TASS news agency that the system demonstrated “high effectiveness during local tactical operations.”

Beskrestnov claims the systems are being sold at the “absolutely magical” price of $1.5 million apiece. While that does not seem prohibitive by American standards, in consideration of the limited area protected, that price point may prevent deployment from being scaled to extend coverage over large areas like the hundreds of miles of highway in southern Ukraine under assault by Starlink-enabled drones.

That Ukraine itself is striking Guarantor systems suggests they are effective enough to be worth attacking, but nonetheless apparently vulnerable to strikes. Besides being targetable at distance with electro-optical guidance, the system’s high-power emissions could also make it vulnerable to emitter-location tactics, including electronic support measures, loitering munitions cued by RF detection, or purpose-built home-on-jam weapons.

Jamming a cloud of gnats

Starlink is notoriously difficult to jam compared to traditional geostationary satellites, for the same reason it is harder to swat a cloud of gnats than an individual fly: it consists of a network of over 10,000 low-Earth orbit satellites that are constantly moving at high speed. Although each satellite remains overhead for roughly five to seven minutes, Starlink’s network timing and beam/satellite management operate on short, synchronized intervals, and user terminals can transition among satellites as geometry changes, complicating attempts to focus jamming on a single moving spacecraft.

This means that a huge number of emitters would be needed to continuously jam Starlink over a wide area; for example, a study by China’s Zhejiang University and Beijing Institute of Technology estimated China would require at least 935 high-powered, or 2,000 low-powered, aerial jamming platforms to deny Starlink across an area the size of Taiwan, or 13,900 square miles.

With its focus on just one satellite at a time, it is not clear how well Russia’s Guarantor overcomes the Starlink “cloud of gnats” challenge. Is an external system continuously re-cueing the Guarantor jammers to target the next most relevant satellite as their orbital positions shift? And if Guarantor only jams one satellite at a time, does that really suffice to ensure another Starlink satellite is not also able to cover that area simultaneously?

It is also worth bearing in mind that Starlink’s jamming resistance extends beyond distributed targeting to other design characteristics, including the ability to adaptively null interference returns from areas generating jamming signals.

Intel on Rossiysky Kupol LLC

A Russian article in March 2025 provides additional details on a C-UAS “super EW” system developed by approximately 150 scientists at Rossiysky Kupol LLC, funded in part by local authorities in Crimea, and allegedly effective against UAS targets at a 20-kilometer radius, or 12.4 miles. Without otherwise mentioning satellite jamming, the article alleges this system “unintentionally suppressed” GPS signals in a neighboring European country, presumably Romania, and allegedly “prevented” an attack by 25 drones targeting a plant near Rostov.

The rise of satellite mega-constellations

It is instructive to observe Russia’s efforts to defend against a distributed satellite mega-constellation, because this technology is not destined to remain uniquely in American hands.

Russia itself is spending approximately $5.3 billion attempting to build a constellation of 292 satellites by 2030 called Rassvet, or “Dawn,” with plans to further scale to 900 satellites. Progress to date has been slow, with 16 operational satellites launched from Plesetsk, one of which has since failed.

Meanwhile, China is advancing three mega-constellations: the commercially oriented Qianfan, or “Thousand Sails,” aiming for 15,000 satellites; the state-owned GuoWang, or “National Network,” a dual-use constellation with 13,000 satellites; and the telecom-oriented Honghu-3, aiming for 10,000 satellites.

Implications for LEO constellation resilience

Guarantor is clearly no panacea. It cannot broadly overcome the distributed redundancy of the Starlink mega-constellation—a single system covering 20 square kilometers against a network of more than 10,000 satellites performing rapid handoffs is, at best, a pinhole defense. Yet the ability to shield a limited, high-value area can still be meaningfully preferable to having no defense at all, and Russian commanders appear to have drawn that same conclusion.

The more consequential lesson is strategic. Russia, China, and the United States all possess broader, not fully disclosed counterspace capabilities, but those tools are rarely available to tactical field commanders. What Guarantor represents is an attempt to bring satellite denial to the unit level—trading coverage breadth for deployability. As LEO mega-constellations multiply and become the backbone of battlefield communications for multiple powers, the tactical demand for localized counter-constellation tools will only grow. The U.S. and its allies, potentially facing adversary LEO networks of comparable scale within a decade, would be prudent to treat Guarantor not as a curiosity but as an early indicator of a new category of tactical electronic warfare.

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