Extended Kalman Filter-Based GNSS Signal Tracking Method to Counter Spoofing Attacks

Under spoofing attacks, the positioning results of GNSS receivers will be towed away. In this study, based on the correlation results of mixed signals, a novel processing model for Kalman Filter-based GNSS code delay tracking loop is proposed. The proposed tracking loop aims to estimate the two sets of correlation peaks and code delays of both GNSS authentic signals and spoofing signals. In the observing model, different from the common KF-based GNSS tracking loop, the measurements are the coherent integrations rather than the DLL discriminator output. Experimental results show that the proposed method is able to estimate the parameters of both authentic signals and counterfeited signals simultaneously. The method can obtain information about the spoofing signal in time, which improves the anti-interference ability of GNSS receiver.