Session A5: Sensor-Fusion for GNSS-Challenged Navigation

Radio SLAM Navigation with Signals of Opportunity in a GPS-Jammed Environment: Sensitivity Analysis and Performance Bounds
Artun Sel, Samer Hayek, and Zak (Zaher) Kassas, The Ohio State University
Location: Beacon A

Over the last few years, GNSS jamming and spoofing incidents have been happening with increasing frequency, exposing the inherent vulnerabilities of GNSS, and rendering them a single point of failure [1]. GNSS jamming and spoofing have affected hundreds of vessels in South Korea; disrupted navigation over the South China Sea islands; caused chaos on smartphones and rideshares in Moscow; put tens of vessels into disarray in the Black Sea; caused dozens of unmanned aerial vehicles (UAVs) to plummet during a Hong Kong air show, resulting in hundreds of thousands of dollars in damages; are suspected to have been utilized to hijack UAVs and oil tankers in the Persian Gulf; disrupted airport operations around the world; and are becoming commonplace in military conflict. What is particularly alarming is that jamming and spoofing are no longer confined to sophisticated rogue organizations, with jammers being sold online and marketed as personal privacy devices, and hackers publishing spoofing software-defined radio (SDR) code online.
Signals of opportunity (SOPs) have been considered to enable navigation whenever GNSS signals become unavailable or unreliable [2]. SOPs are ambient radio signals that are not intended for navigation or timing purposes, such as AM/FM radio [3], [4], cellular [5],[6], digital television [7], [8], and low Earth orbit (LEO) satellite signals [9]–[12]. In contrast to dead-reckoning-type sensors, absolute position information could be extracted from SOPs to provide bounded INS errors [13]. Moreover, many SOPs are practically unaffected by dense smoke, fog, rain, snow, and other poor weather conditions. Among terrestrial SOPs, the most accurate navigation solution has been demonstrated with cellular signals, yielding meter-level navigation on ground vehicles [14] and submeter-accurate navigation on unmanned aerial vehicles (UAVs) [15]. Moreover, cellular signals have been demonstrated to be usable in an intentionally GPS-jammed environment [16].
This paper will showcase results from experiments that took place at Edwards Air Force Base, California, USA, during Navigation Festival (NAVFEST), in which GPS was intentionally jammed with J/S as high as 90 dB. A radio simultaneous localization and mapping (SLAM) approach will be presented along with the experimental results for navigation with cellular SOPs in a GPS-denied environment. In radio SLAM, the vehicle-mounted receiver’s states (position, velocity, clock bias, and clock drift) are simultaneously estimated with the cellular SOPs’ states (position, clock bias, and clock drift).
Experimental radio SLAM results will be presented in an environment under intentional GPS jamming in which the ground vehicle-mounted SOP software-defined receiver (SDR) navigated for 5 km in 180 seconds. Note that to obtain the vehicle’s ground truth trajectory, a vehicle-mounted GNSS-IMU system was used, which utilized signals from the non-jammed GNSS constellations (Galileo and GLONASS). It is shown that the vehicle’ commercial high-end GPS SDR (Septentrio AsteRx-i V) with an industrial-grade IMU (Vectornav VN-100) accumulated a position root mean-squared error (RMSE) of 238 m. On the other hand, the developed SOP SDR was able to acquire and track signals from 7 cellular towers, one of which was more than 25 km away, achieving a two-dimensional position root mean-squared error (RMSE) of 2.6 m exclusively with cellular signals and no other sensors. It is worth noting that the unprecedented 2.6 position RMSE achieved with this SDR are an order of magnitude smaller than previously published results in the same environment [16], which achieved a position RMSE of 29.4 m. The aforementioned results assumed the cellular towers to be mapped a priori (i.e., they have known positions).
Next, the assumption of known SOP positions will be relaxed, and the problem will be formulated as full radio SLAM, in which the positions of these cellular SOP towers will be simultaneously estimated alongside the states of the vehicle. The degradation in position RMSE will be compared to the case when the positions are known a priori. Preliminary results showed that relaxing the assumption of known cellular SOP position to an unknown position (with initial error on the order of hundreds of meters) did not significantly degrade the navigation performance. The rationale behind this is explained in a robust estimation formalism. To this end, a min-max optimization problem is formulated, presenting a tractable solution approach. A sensitivity map is constructed to quantify the positioning error in different regions due to inaccuracies in the transmitters’ positions. Next, assuming the SOPs’ positions uncertainty is known to be bounded by a disk with a known radius ?, an analytic solution is derived for the inaccurate transmitter position within the uncertainty disk, which maximizes the ranging error. Experimental results demonstrate the applicability of the upper-bound in predicting the worst-case vehicle localization performance.

References
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