LAUSR

The spoofing detection algorithm for a global navigation satellite system/inertial navigation system (GNSS/INS) integrated navigation system based on the innovation rate and robust estimation has extensive or invalid detection times, high missed detection rates, and false alarm rates. This study addresses these limitations by proposing a tightly coupled GNSS/INS integration spoofing detection algorithm based on innovation rate optimization and robust estimation. The proposed algorithm improved the normalized innovation of a small step or slow-growing ramp, thereby optimizing its innovation rate test statistics. The proposed approach also reduces the spoofing effect on the innovation rate by adaptively adjusting a gain matrix using robust estimation, thus improving the detection ability further. Simulation results show that the detection time of the proposed algorithm is reduced by 51.9% on average when dealing with small step or slow-growing ramp spoofing. Moreover, the missed detection rate decreased by 58% on average, and the false alarm rate remained at approximately zero. The proposed algorithm has the advantages of fast detection and good performance and is suitable for spoofing detection in unmanned aerial vehicle applications of GNSS/INS integrated navigation systems.