Detection of Spoofing Attacks on Global Navigation Satellite Systems Using Kolmogorov–Smirnov Test-Based Signal Quality Monitoring Method

Signal quality monitoring (SQM) has been widely used as a simple and effective means to detect spoofing attacks on Global Navigation Satellite Systems (GNSS). However, the inherent disadvantages of SQM techniques, such as low detection accuracy and poor robustness, necessitate the study of new methods. We propose an innovative enhanced SQM method based on the application of a statistical test, known as the Kolmogorov–Smirnov (KS) test, applied to monitor the correlator output of the GNSS receiver to identify the subtle distortions of the correlation function. The simulation results show that the KS test-based method is suitable for detecting spoofing attacks with different power advantages. Compared with seven existing typical spoofing detection methods in applied Cases 2, 3, and 7 from the Texas Spoofing Test Battery (TEXBAT) datasets, the proposed method achieved a higher than 95% detection rate at a false alarm rate of 10%, which is 27.69%, 10.36%, and 6.43% higher than that of the detection method based on weighted second-order central moments (WSCMs), respectively, and the spoofed alarm time delay and computation time are shortened. The proposed method overcomes the performance loss of existing SQM methods and provides excellent detection accuracy and effectiveness, thus, can be used as a potential reliable application solution against spoofing attacks with differing frequency lock modes and power superiorities.