An Adaptive Robust Kalman Filtering Method for GNSS/INS Integrated Navigation of High-speed Spinning Vehicle

To address the issue of degraded navigation accuracy in integrated navigation systems due to significant errors in satellite navigation information, caused by high-speed, high-spin, and high-vibration dynamics of the High-speed Spinning Vehicle, an anomaly degree-based fusion filtering method for navigation information is proposed. An adaptive robust Kalman filtering algorithm, based on anomaly degree detection, is designed for the High-speed Spinning Vehicle. Subsequently, a GNSS/INS integrated navigation system is established to improve the navigation accuracy of the High-speed Spinning Vehicle in high-dynamic environments. Experimental results show that the proposed method effectively suppresses the errors of the integrated navigation system under satellite signal limitations, enhancing the robustness and environmental adaptability of the GNSS/INS integrated navigation system.