An applied research of improving Kalman filter in dual mode navigation

被引:0
|
作者
Wu, Zexin [1 ]
Bai, Ming [1 ]
Zheng, Jieling [1 ]
Zhan, Yiyi [1 ]
Xia, Xin Hai [1 ]
Lei, Jie [1 ]
Chen, Zhipeng [1 ]
机构
[1] Guangzhou Maritime Univ, Guangzhou 510725, Guangdong, Peoples R China
关键词
Internet of vehicles; dual mode navigation; Unscented Kalman Filter; M estimation; Extended Kalman Filter;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
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.
引用
收藏
页码:3977 / 3982
页数:6
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