Application of Modified EKF Algorithm in AUV Navigation System

被引：0
|
作者：
Mu, Xiaokai [1 ]
Guo, Jia [1 ]
Song, Yan [1 ]
Sha, Qixin [1 ]
Jiang, Jingtao [1 ]
He, Bo [1 ]
Yan, Tianhong [2 ]
机构：
[1] Ocean Univ China, Sch Informat Sci & Engn, Qingdao, Peoples R China
[2] China Jiliang Univ, Sch Mech & Elect Engn, Hangzhou, Zhejiang, Peoples R China
来源：
OCEANS 2017 - ABERDEEN | 2017年
关键词：
Autonomous Underwater Vehicle; navigation; Extended Kalman filter; Least squares;
D O I：
暂无
中图分类号：
O42 [声学];
学科分类号：
070206 ; 082403 ;
摘要：
The challenge in the Autonomous Underwater Vehicle (AUV) navigation technology is how to ensure precise localization accurately. Extended Kalman filter (EKF) is the most widely used navigation method. Despite its long successful application, EKF has a number of problems in application, for instance, the system motion model usually not appropriate to be described as a linear system. This paper proposed a modified algorithm which combined the Least Squares with Extended Kalman Filter (LS-EKF). The experimental results show that the navigation accuracy of the AUV based on LS-EKF is higher than the EKF.
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页数：4
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