基于最大熵准则的多传感器组合导航融合算法OA

Aiming at the decreasing problem that the filtering accuracy of traditional multi-sensor integrated navigation system information fusion method under non-Gaussian measurement noise,this paper extends Kalman filter based on maximum correntropy criterion(MCCKF)from single integrated navigation system to multi-sensor integrated navigation system,then proposes a sequential centralized fusion algorithm and federated filtering algorithm based on maximum correntropy criterion(MCC).At the same time,it proposes an adaptive kernel bandwidth selection method to optimally deal with non-Gaussian measurement noise and Gaussian measurement noise.The algorithm is verified by the built SINS/GNSS/CNS/ADS integrated navigation system.The experimental results show that the sequential centralized fusion algorithm based on MCC is superior to the federated filtering algorithm based on MCC.Compared with the federated filtering algorithm with fault tolerance function and the traditional centra-lized Kalman filtering algorithm,the sequential centralized fusion algorithm based on MCC can improve position accuracy by 28.4%and 20.1%,and speed accuracy by 15.1%and 12.7%,respectively.