Research on Autonomous Detection Algorithms for Spoofed Interference in Civil Aircraft Airborne Navigation Systems

With the wide application of civil aircraft on-board navigation system, the demand for its safety and stability is increasing. In this paper, the aircraft navigation state data is acquired by GNSS and INS sensors, and the navigation state model is constructed. Through Kalman filtering algorithm, any abnormal or inconsistent navigation state is detected to monitor the real-time performance of the navigation system. When potential deceptive interference is detected, the algorithm is able to take appropriate decisions autonomously, such as switching to an alternate navigation system, sending warning notifications to the flight crew, and so on. In the simulated spoofed interference scenario, the algorithm successfully detected more than 95% of the interference events with an average response time of less than 5 seconds. When the on-board GNSS spoofing causes a position deviation of 250 m or more, the designed algorithm is able to realize a more accurate acquisition of the spoofing duration. The reliability and effectiveness of the proposed algorithm in spoofed jamming scenarios are verified, and the anti-jamming capability of the civil aircraft airborne navigation system is improved.