AUKF-ASVSF in-flight alignment method of SINS based on the GPS/polarization/geomagnetic information

For the low filtering accuracy and robustness of SINS/GPS/polarization/geomagnetic integrated navigation system, an in-flight alignment method based on adaptive unscented Kalman filter-adaptive smooth variable structure filter (AUKF-ASVSF) integrated filter is addressed. Firstly, the error model of SINS/GPS/ polarization/geomagnetic integrated navigation system is established to improve the accuracy of the navigation system by using the information of GPS, polarized light and geomagnetic field. Secondly, according to the innovation sequence, the width of the smooth boundary layer in SVSF algorithm and the measurement noise covariance matrix in UKF algorithm are adaptively adjusted. Finally, the gain of AUKF-ASVSF is calculated based on the width of the smooth boundary layer. Simulation results show that AUKF-ASVSF has stronger anti-interference ability and robustness than UKF and adaptive UKF when the system is subjected to external interference. In addition, the AUKF-ASVSF algorithm has a higher estimation accuracy and faster convergence rate than the traditional UKF-SVSF algorithm when the system measurement noise is unknown. The alignment time of the misalignment angles is reduced by 25.9%, and the alignment accuracy is increased by 11.2%. © 2023 Editorial Department of Journal of Chinese Inertial Technology. All rights reserved.