An applied research of improving Kalman filter in dual mode navigation
Zexin Wu, Ming Bai, Jieling Zheng, Yiyi Zhan, Xin Hai Xia, Jie Lei, Zhipeng Chen · 2017
Aiming at the improvement the low accuracy of conventional Kalman filter, this paper puts forwards a modified Kalman filter to construct a nonlinear regression model based on M estimation, adopts Unscented Kalman Filter (UKF) filtering, and then applies this algorithm to research of dual mode navigation. Experimental results show that the algorithm can improve the navigation accuracy compared with UKF and Extended Kalman Filter (EKF). It retains the high accuracy while the robustness is ensured, it has certain practical application value in dual mode navigation, also has extensive application and broad prospects.