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  • Modern Northstar: Starlink LEO PNT across land, air, stratosphere and Arctic Seas

    Modern Northstar: Starlink LEO PNT across land, air, stratosphere and Arctic Seas

    In January 2015, SpaceX publicly announced its plan to launch Starlink: a mega constellation of nearly 12,000 satellites in low-Earth orbit (LEO) to provide global broadband internet service. In May 2019, the first batch of 60 operational satellites were launched.

    In October 2025, Starlink surpassed 10,000 satellites (see Figure 1). This remarkable achievement means that Starlink has more satellites than all other constellations have ever launched into LEO combined.

    SpaceX is redefining global connectivity, delivering high-speed, low-latency internet anywhere on the planet1. Its civilian system, Starlink, is bridging the digital divide by providing reliable broadband in remote and underserved regions, enabling education, telemedicine and economic growth. Its defense and government variant, Starshield, is offering secure, resilient communications and rapid data transfer for military operations.

    Figure 1 The current constellation of Starlink satellites in LEO, as of January 2026.
    Figure 1 The current constellation of Starlink satellites in LEO, as of January 2026.

    In the midst of the COVID pandemic, in a quiet campus building, the ASPIN Laboratory was busy researching Starlink’s mysterious proprietary signals and the satellites’ poorly known orbits. Having demonstrated the first experimental unmanned aerial vehicle (UAV)2 and ground vehicle3 navigation using Orbcomm LEO satellites, the team’s next grand objective was to exploit Starlink’s signals of opportunity for positioning, navigation, and timing (PNT). At the 2021 ION GNSS+ Conference, the team announced a new era of LEO PNT: the first successful exploitation of Starlink for PNT4. The team designed a cognitive software-defined receiver (SDR) capable of tracking the carrier phase 5 and Doppler6 of Starlink’s so-called pilot tones along with ephemerides error correction algorithms7. The SDR and algorithms were put into test to localize a stationary receiver. Starting from an initial estimate nearly 180 km away, listening to six Starlink satellites resulted in localizing the receiver to within 10 m. This led to worldwide research to study Starlink for PNT, from deciphering Starlink’s downlink orthogonal frequency-division multiplexing (OFDM) signals8,9, to analyzing its ephemerides and timing10,11, to studying the achievable PNT performance12,13.

    This article presents the most advanced LEO PNT results to date with Starlink on four mobile platforms at geographically dispersed locations:

    1. Ground vehicle in Pennsylvania

    2. UAV in Ohio

    3. Extremely high-altitude balloon in New Mexico

    4. Maritime vessel in the Arctic near Greenland

    Exploiting Starlink LEO for PNT: The enablers

    SDR and signal analysis

    Unlike GNSS, non-cooperative LEO satellites such as Starlink do not publicly disclose the structure of their downlink signals, so users must build their own “LEO PNT Interface Control Document (ICD)”14. This can be achieved via “reverse-engineering” the signal. A more powerful approach to “reverse-engineering” is via cognitive SDRs, which employ blind signal processing techniques to learn the signals on-the-fly, regardless of the adopted modulation and multiple-access scheme15.

    The most comprehensive characterization to date of Starlink’s downlink signals for PNT was unveiled in16, utilizing the cognitive SDR approach, in which:

    1. The full OFDM beacon was revealed.

    2. Theoretical and experimental description for exploiting Starlink for PNT was provided, showing the maximum achievable carrier-to-noise density ratio (C/N0) under different scenarios: (i) pilot tones versus OFDM-based beacons and (ii) low-gain versus high-gain reception captures.

    3. A Starlink LEO PNT SDR was designed, yielding the first successful extraction of navigation observables (carrier phase, Doppler shift and code phase) from Starlink’s OFDM signals.

    4. A detailed analysis of the quality of Starlink navigation observables, including (i) signal activity and power levels and (ii) timing corrections that contaminate extracted observables along with mitigation strategies.

    Ephemeris and timing error correction

    Unlike GNSS, non-cooperative LEO satellites, such as Starlink, do not broadcast ephemeris and clock data, so users rely on public sources, such as two-line element (TLE) files. However, this data degrades over time due to orbital perturbations, limiting their effectiveness for PNT. Recent research addressed this challenge through five main approaches:

    1. Differential LEO17,18

    2. Machine learning-based orbit prediction19,20

    3. Measurement error correction21,22

    4. Closed-loop ephemeris tracking23,24

    5. Equivalent timing error compensation25,26

    The next sections will showcase experimental LEO PNT results with Starlink signals of opportunity. All experiments utilized the SDR developed in16 and the ephemerides and timing correction methods developed in26-28.

    Ground vehicle navigation in Pennsylvania

    The experiment was conducted in June 2025. The ground vehicle navigated for 3 km in 120 seconds on Interstate 79 by Pittsburgh, Pennsylvania. GNSS signals were available for the first 30 seconds but were virtually cut off for the last 90 seconds, during which the vehicle traversed a 2.25 km trajectory. The vehicle was equipped with a VectorNav VN-310 dual GNSS/INS operating with real-time kinematic (RTK) corrections and a tactical-grade inertial measurement unit (IMU), from which the vehicle’s ground truth was generated. Starlink signals were captured over all eight Ku-band downlink channels using an upward low-noise block with feed-horn (LNBF) and processed at 2.5 MSps via two NI X410 USRPs.

    Figure 2 shows the ground vehicle’s hardware setup.
    Figure 2 shows the ground vehicle’s hardware setup. shows the ground vehicle’s hardware setup.

    The vehicle navigated by fusing Doppler shift measurements from 11 Starlink satellites in a tightly-coupled fashion to aid the IMU, while altimeter measurements were fused in a loosely-coupled fashion. IMU updates were performed at a rate of 200 Hz. Starlink Doppler measurement updates were performed at a rate of 1 Hz with measurement noise variance inversely related to the received C/N0, ranging between 0.05 (m/s)2 and 6.5 (m/s)2, while altimeter updates were performed at a rate of 10 Hz with a measurement noise variance of 3 m2. The vehicle-mounted receiver and LEO satellites’ oscillator qualities were assumed to be that of an oven-controlled crystal oscillator (OCXO). A prior for the vehicle’s position and velocity was obtained from the on-board GNSS system. Starlink LEO satellites’ ephemeris errors were corrected via the equivalent timing error compensation technique in an online fashion as described in28. Each satellite’s equivalent timing error state was initialized with 0, while the relative clock drift state was initialized as the difference between the measured and predicted pseudorange rate.

    An extended Kalman filter (EKF) was used to estimate the state vector, consisting of the vehicle’s orientation, 3D position, 3D velocity and the IMU’s 3D gyroscope and accelerometer biases along with the relative clock drift error between the receiver and each LEO satellite. The Starlink satellites’ orbits were generated by propagating TLE files with SGP4 for the duration of the experiment. The navigation solution was generated using three approaches:

    1. Unaided IMU: The vehicle navigates via open-loop IMU measurements when GNSS measurements are unavailable.

    2. LEO-aided IMU with TLE+SGP4 ephemerides: The vehicle fuses LEO measurements with IMU and altimeter measurements while incorporating TLE+SGP4 ephemerides in the navigation filter.

    3. LEO-aided IMU with online ephemerides corrections: The vehicle fuses LEO measurements with IMU and altimeter measurements. Starting with TLE+SGP4 ephemerides, the navigation filter estimates an equivalent timing error for each satellite as described in28.

    Figure 3 shows the Starlink satellite trajectories, as well as the vehicle’s ground truth and estimated trajectories with the three navigation approaches. The unaided IMU solution drifted to a 3D position root mean squared error (RMSE) of 258 m from the truth trajectory. The LEO-aided IMU solution that incorporated the erroneous TLE+SGP4 ephemerides resulted in a 3D position RMSE of 150 m, while the navigation solution employing the online ephemeris correction method resulted in an RMSE of 8.41 m. Table 1 summarizes the navigation results.
    Figure 3 shows the Starlink satellite trajectories, as well as the vehicle’s ground truth and estimated trajectories with the three navigation approaches. The unaided IMU solution drifted to a 3D position root mean squared error (RMSE) of 258 m from the truth trajectory. The LEO-aided IMU solution that incorporated the erroneous TLE+SGP4 ephemerides resulted in a 3D position RMSE of 150 m, while the navigation solution employing the online ephemeris correction method resulted in an RMSE of 8.41 m.
    Table 1 summarizes the navigation results.
    Table 1 summarizes the navigation results.

    UAV navigation in Ohio

    The experiment was conducted in August 2025. A DJI M600 UAV navigated for 500 m in 75 seconds in Columbus, Ohio. GNSS signals were available for the first 20 seconds of the experiment but were virtually cut off for the last 55 seconds, during which the UAV traversed a 370 m trajectory. The UAV was equipped with a VectorNav VN-310 dual GNSS/INS operating with RTK corrections and a tactical-grade IMU, from which the UAV’s ground truth was generated. Starlink signals were captured from the 4 low-side Ku-band channels using an upward LNBF and processed at 2.5 MSps via an NI 2955 USRP. Figure 4 shows the UAV’s hardware setup.

    Figure 4 UAV’s hardware setup.
    Figure 4 UAV’s hardware setup.

    The UAV navigated by fusing Doppler shift measurements from nine Starlink satellites in a tightly-coupled fashion to aid the IMU, while altimeter measurements were fused in a loosely-coupled fashion. IMU updates were performed at a rate of 200 Hz. Starlink Doppler measurement updates were performed at a rate of 1 Hz with measurement noise variance inversely related to the received C/N0, ranging between 0.09 (m/s)2  and 6.75 (m/s)2, while altimeter updates were performed at a rate of 10 Hz with a measurement noise variance of 3 m2. The UAV-mounted receiver and LEO satellites’ oscillator qualities were assumed to be that of an OCXO. A prior for the UAV position and velocity was obtained from the UAV’s on-board GNSS system. Starlink LEO satellites’ ephemeris errors were corrected via the equivalent timing error compensation technique in an online fashion as described in 28. Each satellite’s equivalent timing error state was initialized with 0, while the relative clock drift state was initialized as the difference between the measured and predicted pseudorange rate.

    An EKF was used to estimate the state vector, consisting of the UAV’s orientation, 3D position, 3D velocity and the IMU’s 3D gyroscope and accelerometer biases, along with the relative clock drift error between the receiver and each LEO satellite. The Starlink satellites’ orbits were generated by propagating TLE files with SGP4 for the duration of the experiment. The navigation solution was generated using the three approaches described in Section II.

    Figure 5 shows the Starlink satellite trajectories, as well as the UAV’s ground truth and estimated trajectories with the three different navigation approaches. The unaided IMU solution drifted to a 3D position RMSE of 46.51 m from the truth trajectory. The LEO-aided IMU solution that incorporated the erroneous TLE+SGP4 ephemerides resulted in a 3D position RMSE of 17.82 m, while the navigation solution employing the online ephemeris correction method resulted in an RMSE of 8.15 m. Table 2 summarizes the navigation results.

    Figure 5 Experimental results of Doppler-based UAV navigation with Starlink: (a) trajectories of the nine Starlink satellites used to navigate the UAV and (b) UAV’s trajectory (blue) and estimated trajectories via the unaided IMU solution (red) and LEO-aided IMU solutions when incorporating the (i) uncorrected TLE+SGP4 ephemerides (orange) and (ii) online ephemeris correction (green).
    Figure 5 Experimental results of Doppler-based UAV navigation with Starlink: (a) trajectories of the nine Starlink satellites used to navigate the UAV and (b) UAV’s trajectory (blue) and estimated trajectories via the unaided IMU solution (red) and LEO-aided IMU solutions when incorporating the (i) uncorrected TLE+SGP4 ephemerides (orange) and (ii) online ephemeris correction (green).
    Table 2 Experimental results: UAV 3D position errors.
    Table 2 Experimental results: UAV 3D position errors.

    High-altitude balloon navigation in New Mexico

    The experiment was conducted in July 202429. The balloon was launched from the Moriarty Municipal Airport in Moriarty, New Mexico, and landed just south of Mountainair, New Mexico, traveling a horizontal distance of about 105 km south with a 3D distance of about 119 km. The balloon reached a peak altitude of about 25.3 km (83,128 ft) above sea level. A specific time period was studied to evaluate utilization of Doppler observables for navigation at an elevation of 82,177 ft. During this period, five different Starlink satellites were tracked over a 50-second period, during which the balloon traveled 948 m.  The balloon was equipped with a VectorNav VN-200 GNSS/INS, from which the ground truth trajectory was generated. Starlink signals were captured over two Ku-band downlink channels using an upward LNBF and processed at 2.5 MSps via two Ettus B205-mini USRPs. Figure 6 shows the balloon’s hardware setup.

    Figure 6 (a)-(c) High-altitude balloon’s hardware setup. (d) OHIO in New Mexico, left to right: Jennifer Sanderson, Zak Kassas, Will Barrett and the Icarus Balloon. (e) Balloon launch.
    Figure 6 (a)-(c) High-altitude balloon’s hardware setup. (d) OHIO in New Mexico, left to right: Jennifer Sanderson, Zak Kassas, Will Barrett and the Icarus Balloon. (e) Balloon launch.

    The balloon navigated by fusing Doppler shift measurements from five Starlink satellites and altimeter measurements via an EKF. The dynamic model of the high-altitude balloon was chosen as a velocity random walk model, with acceleration process noise spectra set to 0.5 m2/s3 in the in the East, North and 0.8 m2/s3 in the in Up directions, respectively. Starlink Doppler measurement updates were performed at a rate of 10 Hz with measurement noise variance inversely related to the received C/N0, ranging between 1.40 (m/s)2 and 7.01 (m/s)2, while altimeter updates were performed at rate of 10 Hz with a measurement noise variance of 1 m2. The process noise covariance for the clock states was constructed according to an OCXO clock quality. A prior for the balloon’s position and velocity was obtained from the on-board GNSS system. Ephemeris data for each satellite was obtained from offline SGP4-propagated TLE, with epoch time corrections made by minimizing the residuals between predicted Doppler and measured Doppler26,27.

    The EKF state vector consisted of the balloon’s 3D position and 3D velocity along with the relative clock drift error between the receiver and each LEO satellite. The navigation solution was generated using (i) an open-loop approach, which simply propagated the states via the dynamical model and (ii) the LEO+altimeter approach.

    Figure 7 shows the balloon’s ground truth and estimated trajectories with the two different navigation approaches. The open-loop solution drifted to a 3D position RMSE of 83.34 m from the truth trajectory, while the LEO-aided solution resulted in an RMSE of 12.28 m. Table 3 summarizes the navigation results.

    Figure 7 Experimental results of Doppler-based high-altitude balloon navigation with Starlink: (a) trajectories of five Starlink satellites used and (b) balloon’s trajectory (blue) and estimated trajectories via the open-loop solution (red) and LEO-aided solution (green).
    Figure 7 Experimental results of Doppler-based high-altitude balloon navigation with Starlink: (a) trajectories of five Starlink satellites used and (b) balloon’s trajectory (blue) and estimated trajectories via the open-loop solution (red) and LEO-aided solution (green).
    Table 3 Experimental results: High-altitude ballon 3D position errors.
    Table 3 Experimental results: High-altitude ballon 3D position errors.

    Maritime navigation in the Arctic

    The experiment was conducted in August 202430. The vessel navigated for 8.5 km in 20 minutes off the shore of Baffin Island, Nunavut, Canada. Starlink signals were captured over the third Ku-band downlink channel using an upward LNBF and processed at 2.5 MSps via a B205-mini USRP and a Raspberry Pi 4. Figure 8 shows the vessel’s hardware setup.

    Figure 8 Vessel’s hardware setup.
    Figure 8 Vessel’s hardware setup.

    The vessel navigated by fusing Doppler shift measurements from 12 Starlink satellites and altimeter data via an EKF. The dynamic model of the vessel was chosen as a velocity random walk model. Starlink Doppler measurement and altimeter data updates were both performed at a rate of 10 Hz with measurement noise variances of 4.5 (m/s)2 and 3 m2, respectively. The vessel-mounted receiver and the LEO satellites’ oscillator qualities were assumed to be that of an OCXO. The vessel’s position states were initialized from the true position obtained from the on-board GNSS system. The velocity was initialized from the true velocity but with a 10˚ clockwise error with respect to the vessel’s direction-of-motion. The Starlink satellites’ orbits were generated by propagating TLE files with SGP4 for the duration of the experiment. Ephemeris errors were corrected by adjusting the TLE epoch time for eachsatellite26,27 to minimize the residuals between predicted Doppler and measured Doppler.

    An EKF was used to estimate the state vector, consisting of the vessel’s 3D position, 3D velocity and the relative clock drift errors between the receiver and each LEO satellite. The navigation solution was generated via two approaches: (i) using only altimeter data and (ii) using LEO Doppler fused with altimeter data.

    Figure 9 shows the Starlink satellite trajectories, as well as the vessel’s ground truth and estimated trajectories with the two navigation approaches. The altimeter-only solution drifted to a 3D position RMSE of 846 m from the truth trajectory. The LEO+altimeter solution resulted in a 3D position RMSE of 123 m. Table 4 summarizes the navigation results.

    Figure 9 Experimental results of Doppler-based vessel navigation with Starlink: (a) trajectories of the 12 Starlink satellites used to navigate the vessel and (b) vessel’s true trajectory (blue) and estimated trajectories using (i) only an altimeter (red) and (ii) using LEO + altimeter (green).
    Figure 9 Experimental results of Doppler-based vessel navigation with Starlink: (a) trajectories of the 12 Starlink satellites used to navigate the vessel and (b) vessel’s true trajectory (blue) and estimated trajectories using (i) only an altimeter (red) and (ii) using LEO + altimeter (green).
    Table 4 Experimental results: Vessel 3D position errors.
    Table 4 Experimental results: Vessel 3D position errors.

    Acknowledgments

    This work was supported in part by the Office of Naval Research (ONR) under Grants N00014-22-1-2242 and N00014-22-1-2115, in part by the Air Force Office of Scientific Research (AFOSR) under Grant FA9550-22-1-0476, in part by the U.S. Department of Transportation under Grant 69A3552348327 for the CARMEN+ University Transportation Center, in part by The Aerospace Corporation under Award 4400000428, and in part by the Laboratory Directed Research and Development program at Sandia National Laboratories under award 2543953. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DENA0003525. This paper describes objective technical results and analysis. Any subjective views or opinions that might be expressed in the paper do not necessarily represent the views of the U.S. Department of Energy or the United States Government.

    The authors would like to thank Vasilios Konstantacos, Jackson Morris, Ethan Shaw, Khaled Hamil, Aiden Short and Andrew Ye for constructing the balloon’s payload; Mark Andrews for supervising the payload design; and Prabodh Jhaveri, Danny Bowman, Mike Fleigle and Justin LaPierre for helping with launch and recovery of the balloon. The authors would also like to thank The Explorers Club and Adventure Canada for their help with data collection in the Arcitc. The authors would like to thank VectorNav for supplying the VN-200.

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    13. Z. Kassas and J. Saroufim, “LEO PNT frameworks for non-cooperative satellites with poorly known ephemerides: open-loop SGP4, tracking, and differential,” IEEE Aerospace and Electronic Systems Magazine, (40)1, pp. 46-71, 2025.

    14. S. Kozhaya, H. Kanj, and Z. Kassas, “Multi-constellation blind beacon estimation, Doppler tracking, and opportunistic positioning with OneWeb, Starlink, Iridium NEXT, and Orbcomm LEO satellites,” in Proceedings of IEEE/ION Position, Location, and Navigation Symposium, pp. 1184-1195, 2023.

    15. S. Kozhaya, S. Hayek, and Z. Kassas, “Cognitive beacon estimation of unknown LEO satellites signals of opportunity for PNT,” IEEE Journal on Selected Areas in Communications, pp. 1-16, 2026, in-press.

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    Authors

    Zaher (Zak) M. Kassas is the TRC Endowed Chair in Intelligent Transportation Systems and Professor of Electrical and Computer Engineering at The Ohio State University (OSU). He is also Director of the Autonomous Systems Perception, Intelligence, & Navigation (ASPIN) Laboratory and Director of the U.S. Department of Transportation Center for Automated Vehicles Research with Multimodal AssurEd Navigation (CARMEN).

    Samer Hayek is a Ph.D. student at OSU and member of the ASPIN Laboratory.

    Will Barrett was a member of the ASPIN Laboratory.

    Sharbel Kozhaya is a Senior Research Associate at the ASPIN Laboratory.

    Paul El-Kouba is a Ph.D. student at OSU and member of the ASPIN Laboratory.

    Faezeh Mooseli is a Ph.D. student at OSU and member of the ASPIN Laboratory.

    Jennifer Sanderson is a Ph.D. student at OSU and member of the ASPIN Laboratory. She is also an R&D Engineer with Sandia National Laboratories.

    Joe Saroufim is a Ph.D. student at OSU and member of the ASPIN Laboratory.

  • Orkid’s new VTOL drone integrates GNSS, lidar, photogrammetry and Starlink

    Orkid’s new VTOL drone integrates GNSS, lidar, photogrammetry and Starlink

    Drone-maker Orkid has unveiled a new variant of its Orkid 260 drone that incorporates four technologies to improve aerial data-capture technology.

    According to the company, the Orkid 260VTOL represents a leap forward in the integration of advanced sensing and communication technologies, setting a new benchmark for multi-mission drone capability across commercial and industrial applications. The company said it is the “first vertical take-off and landing (VTOL) drone to bring all four of the most advanced aerial data capture technologies together — onboard, fully integrated, and operating simultaneously.”

    The system combines lidar (YellowScan Surveyor Ultra), photogrammetry (Phase One P5 camera), GNSS/IMU (Trimble Applanix APX-RTX), and Starlink satellite communications integration in a single platform.

    Built on a 100% electric, NDAA-compliant architecture, the aircraft delivers an estimated 1.5 hours of flight endurance with a range of up to 75 miles. Designed for mapping, surveying, utilities, oil and gas, defense, and critical infrastructure inspection, the new model expands the operational scope for high-precision, long-range missions.

  • Low-cost antennas power high-precision space-based positioning

    Low-cost antennas power high-precision space-based positioning

    A novel method using signals of opportunity from low-Earth orbit (LEO) satellites is redefining what’s possible in satellite-based navigation. Researchers have developed a joint pseudo-range and Doppler positioning technique that taps into signals from constellations like Starlink and Iridium NEXT — without relying on traditional navigation signal structures.

    By employing low-cost, wide-beam antennas and a specially designed time–frequency inversion algorithm, the team achieved remarkable accuracy: 3.6 meters in 2D and 6.2 meters in 3D, surpassing Starlink positioning approaches based on parabolic antennas by 35%.

    Technical barriers in using signals of opportunity include signal transmission times, low signal power, and imprecise orbital data, all of which hinder accurate positioning. Addressing these challenges demands a new approach to extracting usable navigation data from LEO constellations.

    In response, researchers from the Aerospace Information Research Institute introduced a joint pseudo-range and Doppler positioning method using wide-beam antennas to receive LEO satellite SOPs. The approach centers on a signal time–frequency inversion algorithm that reconstructs key signal parameters, alongside a novel accuracy metric called Equivalent Position Dilution of Precision (EPDOP).

    Real-world experiments combining Starlink Doppler data and Iridium NEXT pseudo-range signals confirmed strong performance, especially in long-baseline conditions — reinforcing the method’s global applicability.

    To overcome the cost and complexity of existing satellite tracking equipment, the team employed low-noise bock (LNB) wide-beam antennas capable of simultaneously receiving signals from multiple Starlink satellites. The core innovation lies in a signal processing algorithm that estimates transmission time and frequency from the received code phase and Doppler shifts — enabling both pseudo-range and Doppler observations without needing exact satellite clock data or real-time ephemeris.

    To quantify system performance under real-world errors, the researchers developed the EPDOP metric, adapted to mixed measurement inputs. Tests demonstrated the method’s robustness: 3.6 m 2D and 6.2 m 3D positioning using Starlink Doppler signals, and up to 24 m (2D) and 41 m (3D) accuracy using Iridium NEXT SOPs over a 40 km baseline. Compared to Doppler positioning techniques, the algorithm reduced positioning errors by over one-third and successfully suppressed the impact of orbital inaccuracies inherent in public two-line element set (TLE) datasets.

    “This work marks a key step toward accessible, accurate navigation using commercial satellite constellations,” said lead author Ying Xu. “By integrating Doppler and pseudo-range measurements and introducing a flexible precision metric, we can now harness Starlink and Iridium NEXT signals for high-precision positioning, even without access to proprietary signal structures. The proposed low-cost architecture opens new possibilities for resilient navigation in GPS-denied environments.”

    Because of its ability to operate with low-cost antennas and weak, unstructured signals, the technique is poised to support a wide range of applications: from autonomous driving and unmanned aerial vehicle (UAV) navigation in remote regions to emergency response and IoT asset tracking. Its resilience to satellite orbital prediction errors and adaptability across different LEO constellations make it a strong contender for next-generation positioning systems. As LEO deployments continue to expand globally, this approach offers a scalable and practical solution for real-time, high-accuracy navigation—promising enhanced capabilities for both civilian infrastructure and defense operations.

    The researchers’ study is published in Satellite Navigation (DOI: 10.1186/s43020-025-00163-y).

    Signal acquisition of Iridium NEXT satellites’ signal in the long baseline positioning scenario. (Credit: Aerospace Information Research Institute)

  • SpaceX details Starlink’s role in enhancing US PNT resilience amid FCC inquiry

    SpaceX details Starlink’s role in enhancing US PNT resilience amid FCC inquiry

    SpaceX has submitted reply comments to the Federal Communications Commission (FCC) detailing how its Starlink low-Earth orbit (LEO) satellite system currently provides, and could further support, positioning, navigation, and timing (PNT) services. The filing is part of the FCC’s ongoing Notice of Inquiry (WT Docket No. 25-110), which seeks to promote resilient and diverse PNT capabilities across the United States in response to vulnerabilities associated with the nation’s reliance on GPS, such as the risks of jamming and spoofing.

    The FCC’s initiative, titled “Promoting the Development of Positioning, Navigation and Timing Technologies and Solutions,” aims to explore both space-based and terrestrial alternatives to ensure the continuity of critical PNT functions for national security, public safety, and economic stability. The agency is soliciting input from stakeholders on technologies that could complement or serve as alternatives to GPS, with a focus on robustness, geographic coverage and resilience to interference.

    In response, SpaceX noted in its comments: “One opportunity stands out as a particularly ripe, low-hanging fruit: facilitating the rapid deployment of next-generation LEO satellite constellations that can deliver PNT as a service alongside high-speed, low-latency broadband and ubiquitous mobile connectivity.”

    SpaceX also states that it has already been working on a PNT system for its cellular Starlink service, which is currently in public beta and is set to launch through T-Mobile in July. SpaceX outlines several technical features of the Starlink system that they argue are relevant to PNT applications.

    Starlink Architecture and Features  

    SpaceX also noted that Starlink terminals can already provide nanosecond-level timing accuracy and meter-level positioning by using time-of-arrival measurements from its satellites. These capabilities allow the network to support precise timing applications, such as cellular network synchronization, without relying on external GPS sources. Timing signals are derived from the LEO constellation and synchronized through Starlink’s broadband infrastructure.

    The filing highlights the Starlink system’s architecture, which includes thousands of satellites in low Earth orbit for global coverage and short signal travel times. SpaceX points to its phased-array user terminals, which use directional antennas to enhance signal integrity and mitigate interference. The company also notes that Starlink employs end-to-end encryption, making its timing and positioning information less susceptible to spoofing or tampering. According to SpaceX, Starlink is already in commercial use by a variety of customers and has been tested by U.S. military and civilian users in environments where traditional GNSS signals are degraded. The company emphasizes that these capabilities have been demonstrated under real-world conditions, not just in theory.

    A Layered Approach to PNT

    Addressing the FCC’s interest in a “layered” approach to national PNT resilience, SpaceX positions Starlink as one of several complementary solutions to enhance national PNT resilience. The company argues that using diverse, independently operated systems — both satellite and terrestrial — can provide redundancy and reduce dependence on any single technology or spectrum band.

    SpaceX also responds to concerns from other stakeholders about whether Starlink qualifies as a PNT system, reiterating that the system was developed independently of government funding and can scale rapidly due to SpaceX’s vertically integrated manufacturing and launch model.

    SpaceX confirms that Starlink operates in Ku- and Ka-band spectrum allocated for broadband services and is not proposing new spectrum allocations for PNT-specific use. It asserts that PNT functionality can be delivered within existing allocation.

  • SpaceX begins partner project designed for national security

    SpaceX begins partner project designed for national security

    Photo:
    Image: 3DSculptor/iStock/Getty Images Plus/Getty Images

    The private spaceflight company, SpaceX, has undertaken a partner project in addition to its existing space efforts ranging from sending satellites and people to space, to providing a brand of commercial internet connection to remote areas.

    The new partner project, Starshield, will join Starlink in providing secure, broadband internet connection to customers. However, there is a stark difference between the partner projects.

    Starlink technology has end-to-end user data encryption to secure its network as it was designed for commercial customers. However, the Starshield project is intended for government use in national security efforts. Therefore, it is equipped with an additional high-assurance cryptographic feature to host payloads and process data in a secure way aligning with government national security requirements.

    As reported by SpaceX, Starshield has three focus areas including: Earth observation, global communications, and hosted payloads. Starshield’s satellites can integrate with a variety of different payloads and the constellation has a low-Earth orbit (LEO) design making it robust to on-orbit assets.

    SpaceX continues to work closely with the United States Department of Defense by providing innovative space technology.

  • Starlink signals can be reverse-engineered to work like GPS

    Starlink signals can be reverse-engineered to work like GPS

    Photo: Official SpaceX Photos
    Photo: Official SpaceX Photos

    A team of researchers from the University of Texas Austin (UTA) have shown the Starlink broadband constellation’s potential to serve as a backup for GPS.

    Todd E. Humphreys headshot
    Todd E. Humphreys

    The researchers, led by Todd Humphreys and funded by the U.S. Army, examined the downlink signal structure of the SpaceX Starlink constellation of ultrafast broadband satellites in low-Earth-orbit (LEO), reported MIT Technology Review. The team showed that Starlink could serve as a useful backup to GPS.

    For the past two years, Humphreys’ team at UT Austin’s Radionavigation Lab has been reverse-engineering signals sent from thousands of Starlink internet satellites to ground-based receivers. Humphreys told the review that regular beacon signals from the constellation, designed to help receivers connect with the satellites, could form the basis of a useful navigation system.

    SpaceX opted not to participate in the research.

    Read the research paper here.

    Title: Signal Structure of the Starlink Ku-Band Downlink

    Authors: Todd E. Humphreys, Peter A. Iannucci, Zacharias Komodromos, Andrew M. Graff

    Abstract: We develop a technique for blind signal identification of the Starlink downlink signal in the 10.7 to 12.7 GHz band and present a detailed picture of
    the signal’s structure. Importantly, the signal characterization offered herein includes the exact values of synchronization sequences embedded in the
    signal that can be exploited to produce pseudorange measurements. Such an understanding of the signal is essential to emerging efforts that seek to dual-purpose Starlink signals for positioning, navigation, and timing, despite their being designed solely for broadband internet provision.

  • U‑blox and ERM launch vehicle-tracking device with built-in Wi‑Fi hotspot

    U‑blox and ERM launch vehicle-tracking device with built-in Wi‑Fi hotspot

    Photo: ERM/u-blox
    Photo: ERM/u-blox

    U‑blox has released the StarLink TrackerWi‑Fi, an advanced vehicle-tracking device produced by ERM Advanced Telematics, a provider of device-based telematics solutions.

    The device combines u-blox GNSS, 4G and Wi-Fi technology, eliminating the need to equip vehicles with a separate mobile Wi‑Fi hotspot.

    According to the companies, the StartLink TrackerWi‑Fi is suitable for applications for connected cars, telematics, vehicle diagnostics, fleet management, vehicle security, usage-based insurance, and rental and leasing service companies.

    The internet of things (IoT) and connected-car initiatives are providing rental car companies and transportation and logistics firms with tools to track vehicles, preemptively detect and diagnose disturbances from a distance, and monitor the behavior of their drivers in real time. ERM has more than 1.8 million vehicle fleet-tracking devices deployed on roads world-wide.

    As onboard Wi‑Fi becomes increasingly widespread, many companies are fitting vehicles with Wi‑Fi hotspots to offer drivers and passengers internet access. With its integrated Wi‑Fi hotspot, ERM’s StarLink TrackerWi‑Fi lets users tap into the cellular 4G connectivity to transfer telematics data to the fleet manager. This makes it possible to send real-time telematics data to the driver’s smart device or onboard infotainment system, and it also reduces the number of SIM cards needed from one per device to one per vehicle.

    Sourcing the GNSS tracking, cellular 4G LTE, and Wi‑Fi technology from u-blox played a key role in achieving the device’s fast time to market. By using u‑blox’s pre-tested positioning and communications modules with integrated software, the manufacturer was able to cut the time needed for production and development by several months.

    “We saw an opportunity to provide more values to our customers by adding Wi‑Fi hot spot functionality to our StarLink Tracker, our leading telematics product, but knew that we had to be quick to stay ahead of the game,” said Kfir Lavi, senior vice president of ERM Advanced Telematics.

    “Our partners are always at the top of our priorities, and we are working to adapt our offerings to the market demands and the changing needs of their customers. Working with u‑blox as the provider of the positioning and wireless communication technology helped us move from concept to commercialization in under six months and provide our partners with an advanced product in a short time,” Lavi said.

    “This successful collaboration demonstrates that we have evolved from a provider of individual technologies, namely GNSS positioning, cellular 4G connectivity, or short range radio communication, to a provider of solutions that bundle these technologies,” said Thomas Seiler, CEO of u-blox. “We are seeing increased demand for such bundled solutions and are convinced that the close integration of our technology portfolio offers our customers the unique ability to jump-start even challenging projects on extremely short notice.”

  • Forsberg Acquires Raven’s StarLink GNSS Product Line

    Forsberg Services Ltd. has acquired the StarLink product line from Raven Industries. StarLink includes inline amplifiers, coaxial down/up converters and fiber-optic link systems to enable and support extended cable runs for GNSS in navigation and time synchronization applications.

    Raven Industries' Starlink GPS down/up converter makes it possible for long cable runs of 450 meters up to 1.6 kilometrers.
    Raven Industries’ Starlink GPS down/up converter makes it possible for long cable runs of up to 450 meters.

    “This opportunity provides an excellent addition to complement our range of GNSS products and services,” said Chris Mayne, Forsberg operations director. “We have worked closely with Raven Industries as a distributor of the StarLink products for the last three years and appreciate the opportunity to take the product brand forward with its customary high quality and standards.”

    Forsberg Services Ltd. is a European navigation systems integrator and OEM component supplier based in Lancaster, U.K and with offices near Hannover, Germany. The company has strong engineering experience in navigation; specializing in PCB, software and mechanical design to produce unique navigation products for a range of applications and market sectors.

    For more information, visit the Forsberg Servics website, email [email protected] or call +44-1524-383320.