Detection of slowly varying spoofing using weighted Kalman gain in GNSS/INS tightly coupled systems

Global Navigation Satellite System (GNSS) is vulnerable to intentional spoofing attacks, particularly those that vary slowly over time. These attacks aim to deceive receivers by introducing subtle changes to the received signals, making them hard to detect using traditional methods. To tackle this challenge, we propose an improved slowly varying spoofing detector that uses a weighted Kalman gain to enhance the sensitivity of the extended Kalman filter (EKF) to slowly varying spoofing. Our detector addresses the limitations of the conventional EKF, which does not account for the impact of spoofing on the innovation offsets, leading to rapid induction of the filtering results. By weighting the EKF gain based on the normalized distance between the test statistic of each satellite and the detection threshold, our proposed detector mitigates harmful satellite innovations and accumulates the innovation offsets caused by spoofing. Simulation and experimental results demonstrate that the proposed detector achieves a higher detection probability and sensitivity compared to existing methods. Our proposed detector offers a novel approach to detect slowly varying spoofing and represents a significant contribution to the field of GNSS security.