Research on GNSS/INS Vector Deep Integration Algorithm

This paper proposes a GNSS/INS vector deep integration navigation filtering method based on the Adaptive Square Root Cubature Kalman Filter (ASRCKF) to address challenges such as satellite loss, signal interruptions, and degraded positioning accuracy in complex environments. The method enhances robustness using M-estimation and the IGG III weight function. Experimental results show that the ASRCKF-based vector tracking loop ensures continuous and stable signal tracking in dynamic conditions and significantly improves positioning accuracy in noisy environments compared to conventional filtering methods.