Abstract Integrated navigation system has strong nonlinear characteristic in dynamic environment, so we propose an optimal multi-sensor fusion algorithm based on sequential UKF to improve the navigation accuracy of GNSS/CNS/SINS integrated navigation system. Firstly, we establish the nonlinear state equation and the linear measurement equations of two subfilters for GNSS/CNS/SINS integrated navigation system. Then, by simplifying the measurement updating process of the standard UKF algorithm, we design a simplified UKF algorithm that has the same filtering accuracy as the standard UKF algorithm and has characteristics of low computation. Finally, we propose the sequential UKF optimal fusion algorithm for multi-sensor integrated navigation system, by combining the sequential filtering algorithm with the simplified UKF algorithm. The simulation results show that the sequential UKF algorithm not only improves the real-time performance of the system, but also has higher filtering accuracy than the conventional centralized Kalman filter algorithm and the classical centralized linear UKF algorithm.
LIN Xueyuan,WANG Ping,XU Jialong et al. An Optimal Fusion Algorithm for GNSS/CNS/SINS Integrated Navigation Based on Sequential UKF[J]. jgg, 2022, 42(12): 1211-1215.
LIN Xueyuan,WANG Ping,XU Jialong et al. An Optimal Fusion Algorithm for GNSS/CNS/SINS Integrated Navigation Based on Sequential UKF[J]. jgg, 2022, 42(12): 1211-1215.