Adaptive Robust Kalman filter for AUV Polar Integrated Navigation
Zhonghong Liang, Ming Tian, Zhikun Liao, Chongwei Wang, Jingsui Li · 2022
AUV (Autonomous Underwater Vehicle) plays an growing essential role in the field of ocean exploration in polar regions. Due to the rapid convergence of meridians, traditional inertial navigation methods fail in polar regions. To tackle this problem, an INS/DVL integrated navigation system based on the transverse frame is designed in this article. Since the DVL noise is unknown and time-varying, the RKF (Robust Kalman filter) algorithm based on Mahalanobis distance is used to estimate the measurement noise adaptively. The method was proven effective in mid-latitude and polar regions through ship and semi-physical experiments. RKF can effectively avoid the influence of DVL outliers and improve positioning accuracy.