Light will Guide You: Passive Joint DOA/FOA Sensing, Tracking, and Navigation with Unknown LEO Satellites

Sharbel Kozhaya, Joe Saroufim, Samer Hayek, Paul El-Kouba, and Zaher Kassas

Peer Reviewed

Abstract:	The potential of signals of opportunity (SOPs) as a reliable navigation source has been undoubtedly uncovered in the past decade. Previous literature showed meter-level accurate ground vehicle navigation [1-4] and sub-meter-level accurate unmanned aerial vehicle (UAV) navigation with cellular SOPs [5, 6]. Exploiting SOPs did not stay earthly; nowadays, space vehicles are considered potential SOPs to complement the global navigation satellite system (GNSS). Several theoretical and experimental studies characterized broadband low Earth orbit (LEO) satellite signals as possible, reliable sources for navigation [7-10]. LEO satellites possess desirable attributes for positioning in GNSS-challenged environments: (i) they are around twenty times closer to the Earth compared to GNSS satellites, which reside in medium Earth orbit (MEO), making their received signal power between 24 to 34 dB higher than GNSS signals; (ii) they are becoming abundant as thousands of broadband Internet satellites are expected to be deployed into LEO [8]; and (iii) deployed broadband LEO satellites transmit at different frequency bands, making LEO satellite signals diverse in frequency and direction [1]. While such results bring hope to solving the problem of reliable navigation in GNSS-challenged environments, one must emphasize that navigating with LEO satellites comes with several challenges. The main challenges are the absence of (i) publicly available receivers that can extract navigation observables from LEO satellite signals, (ii) source of error characterization for designing LEO satellite navigation frameworks, namely clock’s stability and position determination using orbit propagators, and (iii) performance analyses tools to evaluate these frameworks. Moreover, the Keplerian elements parameterizing the orbits of these LEO satellites are made publicly available by the North American Aerospace Defense Command (NORAD) and are updated daily in the two-line element (TLE) files. Using TLEs and orbit determination algorithms (e.g., simplified general perturbation 4 or SGP4), the positions and velocities of these satellites can be known, albeit not precisely. Some broadband LEO constellations have publicly available transmission schemes and broadcast their positions from onboard GPS receivers, such as Orbcomm. Other broadband LEO constellations have dedicated positioning solutions embedded in their systems; however, they charge for subscriptions to access their data, such as Iridium NEXT. Finally, some LEO constellations operated by private companies are optimized solely for communication purposes and do not broadcast navigation frames, such as Starlink and OneWeb. Furthermore, most LEO constellation companies employ the bent pipe system, which allows them to upgrade and change their transmission scheme when needed, such as Globalstar, Starlink, and OneWeb. This paper proposes a framework that: (i) opportunistically exploit the signal from broadband LEO satellites and (ii) attempt to track these satellites in a closed loop fashion to refine their estimated position. In the first contribution, this paper aims to develop a blind LEO receiver agnostic to the modulation scheme used (M-ary PSK, ODFM, or other) and the dynamics of the satellite. At the core of the blind receiver is the ability to detect periodically transmitted signals, estimate and track them, and finally generate navigation observables. One can be reasonably confident that beacons are present in every communication system. For example, a primary and secondary synchronization sequence (PSS) and (SSS), respectively, are transmitted in 4G LTE and 5G NR systems for symbol timing recovery. Such sequences were exploited for opportunistic navigation purposes [3, 12]. However, in such cases, those repeated sequences are published and maintained by the 3rd Generation Partnership Project (3GPP), and it is assumed that the receiver perfectly knows the synchronization sequences and can correlate local replicas of these sequences with the received signals. In the case where these sequences are unknown, as in the case of future broadband LEO satellite systems, acquiring and tracking these satellite signals becomes impossible for a regular opportunistic receiver, as such, designing receivers that can blindly and adaptively estimate these sequences is a crucial need for the future of opportunistic navigation. The problem of detecting and estimating periodically transmitted signals is not new in the literature. Successful blind Orthogonal Frequency Domain Multiplexing (OFDM) symbol timing recovery methods have been employed in the wireless communications and cognitive radio literature [13-15]. Furthermore, blind receiver in [16] was used to detect 5G and LTE signals and navigate with meter-level position root-mean-squared error (RMSE). However, the proposed approaches make assumptions that do not hold for the case of LEO satellite transmitters, mainly the low magnitude of the frequency offset and stationarity of the channel. Unfortunately, Doppler frequencies of 240 kHz or more could be observed for LEO satellites transmitting in the Ku band. As a result of the high dynamics of LEO satellites, it is almost impossible to coherently integrate the signal to accumulate enough power for reliably detecting the synchronization signals. While other approaches rely on large and expensive high-gain antennas to accumulate enough power for a single snapshot [17], this work aims at developing a framework for low-cost, online estimation of synchronization sequences in signals. Several research successfully developed some blind techniques to extract Doppler observables from received LEO signals and generate navigation solutions with them. For instance, experimental results presented in [18] shows a UAV navigating with signals from 2 Orbcomm LEO satellites over 2 minutes using carrier differential framework. In that paper, a blind Doppler tracking approach was employed, and the resultant doppler was integrated to form carrier phase observables. Furthermore, a navigation solution was generated using the blind receiver's observables and compared against another navigation solution generated using a dedicated Orbcomm receiver's observables. A GNSS-INS navigation solution was used a baseline for comparison. Additionally, another Doppler acquisition and tracking algorithm was proposed in [19] and tested on Orbcomm and Iridium NEXT LEO satellites. However, all the aforementioned proposed frameworks so far rely on the knowledge of the structure of the signals transmitted by Orbcomm and Iridium satellites that use M-ary Phase Shift Keying (M-ary PSK) modulation [20, 21] and fail to work on OFDM-based constellations such as Starlink and OneWeb. The proposed receiver will learn the transmitted repetitive sequences on-the-fly in a blind fashion and generate navigation observables such as carrier phase, Doppler, pseudorange, and their respective carrier-to-noise density ratio. In the second contribution, this paper aims to develop a framework for passive RF tracking of LEO satellite based on pseudorange and Doppler measurements generated by the blind receiver. Experimental results of real-time tracking of LEO satellites will be demonstrated and the estimate satellite position will be compared with the publicly available TLE files to quantify the performance of this passive RF tracking framework. [1] C. Yang, T. Nguyen, and E. Blasch, “Mobile positioning via fusion of mixed signals of opportunity,” IEEE Aerospace and Electronic Systems Magazine, vol. 29, no. 4, pp. 34–46, April 2014. [2] J. Khalife and Z. Kassas, “Precise UAV navigation with cellular carrier phase measurements,” in Proceedings of IEEE/ION Position, Location, and Navigation Symposium, April 2018, pp. 978–989. [3] K. Shamaei, J. Khalife, and Z. Kassas, “Exploiting LTE signals for navigation: Theory to implementation,” IEEE Transactions on Wireless Communications, vol. 17, no. 4, pp. 2173– 2189, April 2018. [4] Z. Kassas, J. Khalife, K. Shamaei, and J. Morales, “I hear, therefore I know where I am: Compensating for GNSS limitations with cellular signals,” IEEE Signal Processing Magazine, pp. 111–124, September 2017. [5] A. Abdallah and Z. Kassas, “Precise uav navigation with 5G carrier phase measurements,” in Proceedings of ION GNSS Conference, September 2021, accepted. [6] K. Shamaei and Z. Kassas, “Sub-meter accurate UAV navigation and cycle slip detection with LTE carrier phase,” in Proceedings of ION GNSS Conference, September 2019, pp. 2469–2479. [7] M. Joerger, L. Gratton, B. Pervan, and C. Cohen, “Analysis of Iridium-augmented GPS for floating carrier phase positioning,” NAVIGATION, Journal of the Institute of Navigation, vol. 57, no. 2, pp. 137–160, 2010. [8] T. Reid, A. Neish, T. Walter, and P. Enge, “Broadband LEO constellations for navigation,” NAVIGATION, Journal of the Institute of Navigation, vol. 65, no. 2, pp. 205–220, 2018. 5 [9] J. Morales, J. Khalife, and Z. Kassas, “Simultaneous tracking of Orbcomm LEO satellites and inertial navigation system aiding using Doppler measurements,” in Proceedings of IEEE Vehicular Technology Conference, April 2019, pp. 1–6. [10] J. Khalife and Z. Kassas, “Assessment of differential carrier phase measurements from orbcomm LEO satellite signals for opportunistic navigation,” in Proceedings of ION GNSS Conference, September 2019, pp. 4053–4063. [11] D. Lawrence, H. Cobb, G. Gutt, M. OConnor, T. Reid, T.Walter, and D. Whelan, “Navigation from LEO: Current capability and future promise,” GPS World Magazine, vol. 28, no. 7, pp. 42–48, July 2017. [12] M. Driusso, C. Marshall, M. Sabathy, F. Knutti, H. Mathis, and F. Babich, “Vehicular position tracking using LTE signals,” IEEE Transactions on Vehicular Technology, vol. 66, no. 4, pp. 3376–3391, April 2017. [13] M. Tanda, “Blind symbol-timing and frequency-offset estimation in OFDM systems with real data symbols,” IEEE Transactions on Communications, vol. 52, no. 10, pp. 1609–1612, October 2004. [14] A. Al-Dweik, “A novel non-data-aided symbol timing recovery technique for OFDM systems,” IEEE Transactions on Communications, vol. 54, no. 1, pp. 37–40, January 2006. [15] W. Liu, J. Wang, and S. Li, “Blind detection and estimation of OFDM signals in cognitive radio contexts,” in International Conference on Signal Processing Systems, vol. 2, July 2010, pp. 347–351. [16] M. Neinavaie, J. Khalife, and Z. Kassas, “Cognitive opportunistic navigation with 5G signals and beyond,” IEEE Journal of Selected Topics in Signal Processing, 2021, submitted. [17] G. Gao, “Towards navigation based on 120 satellites: Analyzing the new signals,” Ph.D. dissertation, Stanford University, 2008. [18] M. Neinavaie, J. Khalife, and Z. Kassas, “Blind Doppler tracking and beacon detection for opportunistic navigation with LEO satellite signals,” in Proceedings of IEEE Aerospace Conference, March 2021, pp. 1–8. [19] F. Farhangian and R. Landry, “Multi-constellation software-defined receiver for Doppler positioning with LEO satellites,” Sensors, vol. 20, no. 20, pp. 5866–5883, October 2020. [20] Orbcomm, https://www.orbcomm.com/en/networks/satellite. [21] Iridium Constellation LLC, “Iridium NEXT engineering statement,” http://licensing.fcc.gov/ myibfs/download.do?attachment key=1031348. [22] A. Tadaion, M. Derakhtian, S. Gazor, M. Nayebi, and M. Aref, “Signal activity detection of phase-shift keying signals,” IEEE Transactions on Communications, vol. 54, no. 8, pp. 1439– 1445, August 2006. [23] K. Shamaei, J. Khalife, and Z. Kassas, “Performance characterization of positioning in LTE systems,” in Proceedings of ION GNSS Conference, September 2016, pp. 2262–2270.
Published in:	2025 IEEE/ION Position, Location and Navigation Symposium (PLANS) April 28 - 1, 2025 Salt Lake Marriott Downtown at City Creek Salt Lake City, UT
Pages:	716 - 727
Cite this article:	Kozhaya, Sharbel, Saroufim, Joe, Hayek, Samer, El-Kouba, Paul, Kassas, Zaher, "Light will Guide You: Passive Joint DOA/FOA Sensing, Tracking, and Navigation with Unknown LEO Satellites," 2025 IEEE/ION Position, Location and Navigation Symposium (PLANS), Salt Lake City, UT, April 2025, pp. 716-727.
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