Analysis of Kalman Filter Innovation-Based GNSS Spoofing Detection Method for INS/GNSS Integrated Navigation System

GNSS spoofing is an emerging threat to navigation systems. INS/GNSS integrated navigation, which is the most widely used baseline navigation configuration, has the potential to detect GNSS spoofing attacks effectively. This paper focuses on the Kalman filter innovation-based spoofing detection method, which can be easily applied to the integrated navigation systems. Measurement averaging and innovation averaging techniques used in the autonomous integrity monitored extrapolation method are revisited from the perspective of GNSS spoofing detection, with a focus on the detailed derivation of measurement averaging and a comparison of these two averaging processes. Monte Carlo simulations are carried out to verify our analysis, which shows the effectiveness of the Kalman filter innovation-based spoofing detection method against ramp-type fault profiles and the advantages of measurement averaging over innovation averaging in certain spoofing scenarios.