ARPSO-MLE based GNSS anti-spoofing method

Maximum likelihood estimation (MLE) has been used in direct position estimation in the global navigation satellite system (GNSS) receivers. It can be used for anti-spoofing because it utilizes the consistency between different satellites. In the method, how to find the optimal MLE solution is a challenge, because the likelihood function of the MLE is multimodal. In the paper, particle swarm optimization (PSO) is used in the multimodal optimization problem. Further, attractive and repulsive PSO (ARPSO) is used to overcome the premature convergence in the basic PSO. The performance of the ARPSO is compared to that of a basic PSO and the SAGE method. The average position accuracy of different methods under scenes with 1 to 3 spoofing signals is given based on computer simulations. Results show that with initial position and time uncertainty introduced by the spoofing attack, the proposed ARPSO-MLE method for direct position estimation can provide navigation solution with accuracy better than 10 meters in the range of medium to high signal-to-noise ratio (SNR) under spoofing attacks.