Session A2: GNSS Security: Interference, Jamming, and Spoofing 1

Performance of Optimal INS Monitor Against Live Spoofing
Birendra Kujur, Samer Khanafseh, Boris Pervan, Illinois Institute of Technology
Location: Beacon A

In this paper, we demonstrate the performance of the proposed optimal Inertial Navigation System (INS) monitor [19] against live spoofing with multiple Global Navigation Satellite System (GNSS) spoofing scenarios. We evaluate the monitor performance for a live spoofing event. An aircraft was subjected to live GNSS spoofed signals using onboard equipment during its flight with different spoofed trajectories such as step, ramp, and accelerating position offsets. The spoofing signals were generated and broadcast on a single frequency GPS constellation while spoof-free GNSS signals were acquired using other constellations. Spoofed GPS signals, spoof-free GNSS signals, and Inertial Measurement Unit (IMU) dynamic data was collected. From preliminary results we show that the optimal INS monitor can detect spoofing even at sub-decimeter level magnitudes within minutes. As a result, the conducted experiments demonstrate the monitor’s ability to detect realistic GNSS spoofing events even with minimal position offsets, thereby validating the performance of the monitor.
The civil infrastructure of safety critical fields such as aviation, maritime and terrestrial navigation rely on GNSS. This brings a major responsibility to ensure absolute GNSS integrity. The civil GNSS signal structure is publicly known and vulnerable to spoofing attacks, which endangers public safety [1]. Spoofing attacks consist of intentional jamming of the authentic radio-frequency signals and feeding a predetermined faulty signal to the user. The fault can be injected to cause gradual position or time offsets. Potential detection techniques include signal processing techniques, cryptographic authentication [2], spoofing discrimination using spatial processing by antenna arrays, and automatic gain control schemes [3], [4], GNSS signal direction of arrival comparison [5], code and phase rate consistency checks [6], high-frequency antenna motion [7], and signal power monitoring techniques [8]. Some of these methods are indeed effective but they have various computational, logistical and physical limitations.
Augmenting data from auxiliary sensors such as Inertial Measurement Units (IMU), barometric altimeters, and independent radar sensors to discriminate spoofing has also been proposed [9], [10]. The first stochastic description and quantification of the performance of IMU-based GNSS spoofing monitor against worst-case faults was introduced by us [11-17]. We specifically investigated anti-spoofing solutions utilizing IMUs, since all modern vehicles are equipped with them, thereby requiring minimal additional cost or system modification. An IMU is immune to external interference, which makes it the best candidate for counter measure against GNSS spoofing attacks. INS, when used in the navigation solution in various integration schemes with GNSS (such as uncoupled, loosely-, tightly-, or ultra-tightly coupled), provides redundancy to the system, which is a direct means of resisting spoofing attacks.
To specifically address the most difficult to detect scenario where a spoofer replicates the authentic GNSS signal with only additive errors due to the spoofer’s uncertainty and latency in knowledge of the target’s position, we developed an optimal INS monitor [19]. The monitor accumulates the spoofer’s target tracking errors over time to detect the anomalous temporal structure of the spoofed measurements. We provided an analytical method for determining the length of the monitor window that would ensure detection of tracking error with a given missed detection probability. We evaluated the performance of the monitor with tracking errors modeled as both white and colored Gaussian noise and showed detectability of centimeter level tracking error noise with a low probability of missed detection (10^(-7)) and false alarm (10^(-5)). We also experimentally validated the performance of the optimal monitor with simulated spoofing scenarios [20].
To validate the monitor performance under realistic spoofing scenarios, GNSS measurements and IMU data for an aircraft under live spoofing are collected. These spoofed GNSS measurements along with the IMU data are then used in the tightly coupled Kalman Filter through which the optimal monitor’s performance is evaluated. Preliminary results show that the monitor can detect spoofing even with sub-decimeter level offsets within minutes for different spoofing profiles. This demonstrates that the optimal monitor can successfully detect realistic spoofing in real-life environment.

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[19] B. Kujur, S. Khanafseh, and B. Pervan, “Optimal INS Monitor against GNSS spoofer Tracking Error Detection,” NAVIGATION: Journal of the Institute of Navigation Mar 2024, 71 (1) navi.629
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