基于最大熵准则的GNSS/SINS组合导航滤波算法OA北大核心CSTPCD

The traditional Kalman filter(KF)of GNSS/SINS integrated navigation system is optimal under the minimum mean square error(MMSE)criterion and under the Gaussian hypothesis.Howev-er,when the measurement noise is disturbed by heavy tail pulse noise,the filtering performance of KF is seriously degraded.To solve this problem,we propose a maximum entropy Kalman filter(MCKF)for integrated navigation system.First,we establish the state equation and measurement equation of MCKF.Then,using the principle of maximum entropy,we establish a Kalman filter based on the maximum entropy criterion,and design its filter iteration flow.Finally,we simulate the GNSS/SINS integrated navigation system in the environment of mixed Gaussian noise and heavy tail pulse noise,respectively.The simulation results show that KF performs better than MCKF under mixed Gaussian noise interference,MCKF has better filtering performance than KF under the interference of heavy tail pulse noise,and MCKF is equivalent to KF when the kernel bandwidth tends to infinity.