Underwater terrain-aided navigation method based on improved Gaussian sum particle filtering

被引:12
作者
Chen, Pengyun [1 ]
Chang, Jianlong [1 ]
Han, Yujie [2 ]
Yuan, Meini [1 ]
机构
[1] North Univ China, Coll Mechatron Engn, Taiyuan 030051, Shanxi, Peoples R China
[2] AVIC Mfg Technol Inst, Beijing, Peoples R China
来源
INTERNATIONAL JOURNAL OF ADVANCED ROBOTIC SYSTEMS | 2019年 / 16卷 / 01期
基金
中国国家自然科学基金;
关键词
Terrain-aided navigation; underwater environment; Gaussian sum particle filtering; RBF neural network;
D O I
10.1177/1729881418821576
中图分类号
TP24 [机器人技术];
学科分类号
080202 ; 1405 ;
摘要
To solve the nonlinear Bayesian estimation problem in underwater terrain-aided navigation, a terrain-aided navigation method based on improved Gaussian sum particle filter is proposed. This method approximates the Bayesian function using multiple Gaussian components, and the components can be obtained by radial basis function neural network. This method has no resampling process, the particle depletion of particle filtering is eliminated in principle. The simulation shows that the proposed method has good matching performance, which is suitable for autonomous underwater vehicle navigation.
引用
收藏
页数:7
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