A Self-adaptive Unscented Kalman Filtering for Underwater Gravity Aided Navigation

被引：0

作者：

Wu, Lin ^{[1
]}

Ma, Jie ^{[1
]}

Tian, Jinwen ^{[1
]}

机构：

[1] Huazhong Univ Sci & Technol, Inst Pattern Recognit & Artificial Intelligence, State Key Lab Multispectral Informat Proc Technol, Wuhan 430074, Peoples R China

来源：

2010 IEEE-ION POSITION LOCATION AND NAVIGATION SYMPOSIUM PLANS | 2010年

关键词：

underwater gravity aided navigation; unscented Kalman filter; autonomous underwater vehicle; gravitational field maps; inertial navigation system;

D O I：

暂无

中图分类号：

U6 [水路运输]; P75 [海洋工程];

学科分类号：

0814 ; 081505 ; 0824 ; 082401 ;

摘要：

In this paper, a self-adaptive unscented Kalman filtering for underwater gravity aided navigation is constructed. It is more accurate and far easier to implement than an extended Kalman filter. Then the novel navigation algorithm based on the self-adaptive unscented Kalman filter is explored. With this method submerged position fixes for autonomous underwater vehicle can be obtained from comparing gravity fields' measurements with gravity maps. Specifically, simulation results show that navigation errors can be reduced more effectively and efficiently by the presented algorithm.

引用

页码：984 / 987

页数：4

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