Adaptive Resilience Navigation Filter for Detecting and Mitigating Multi-Spoofing Attacks in Range-Based Localization Systems using Antenna Arrays

Ensuring the integrity of range-based localization systems is crucial, particularly due to their pervasive use in critical civilian and military applications and their vulnerability to sophisticated spoofing attacks. Among these, multi-spoofer attacks, involving coordinated and strategically positioned spoofers capable of manipulating signals to evade detection, represent a significant operational threat. This paper investigates filtering approaches to enhance the resilience of vehicles equipped with directional receivers, such as antenna or hydrophone arrays, against such advanced threats. To address this challenge, it introduces the Adaptive Resilience Navigation Filter (ARNF), designed to detect ongoing attacks, identify compromised signals, and mitigate their effects. Leveraging statistical hypothesis testing and single phase differences from antenna array measurements, the ARNF dynamically adapts to spoofed and non-spoofed signals to estimate biases introduced by spoofers and restore navigation accuracy. Validation through simulations under realistic Global Navigation Satellite System (GNSS) conditions demonstrates the efficacy of the ARNF, with performance compared to the 2-Stage Extended Kalman Filter and the ideal Clairvoyant Extended Kalman Filter.