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An underwater mining navigation method based on an improved particle filter
Alternative Title一种基于改进粒子滤波的水下采矿导航方法
Zhang ZH(张志慧)1,2,3; Feng YB(冯迎宾)1,2; Li ZG(李智刚)1,2; Zhao XH(赵小虎)1,2,3; Zhang ZH(张志慧)4,5,6; Feng YB(冯迎宾)4,5; Li ZG(李智刚)4,5; Zhao XH(赵小虎)4,5,6
Department水下机器人研究室
Source Publication中国科学院大学学报
ISSN2095-6134
2020
Volume37Issue:4Pages:507-515
Indexed ByCSCD
CSCD IDCSCD:6763560
Contribution Rank1
Funding OrganizationNational Key Research and Development Program of China (2016YFC0304102-6)
Keywordparticle filter ( PF) resampling underwater mining navigation particle degeneration particle impoverishment
Abstract

An underwater mining navigation method based on an improved particle filter ( PF) is proposed to solve the problems of non-Gaussian and intense measurement noise during underwater mining,and a new resampling algorithm is designed,as an improvement,to eliminate the influences of particle degeneration and particle impoverishment of PF. Compared to the resampling algorithms, the proposed algorithm avoids particle impoverishment and improves estimation accuracy. Finally, the estimation accuracies of underwater mining navigation algorithms based on the improved PF and the unscented Kalman filter ( UKF) are compared by combining the lake trial data and underwater mining navigation model. The results of simulation experiments manifest that the proposed method has more accurate estimation and remarkable robustness.

Other Abstract

针对水下采矿导航系统所面临的噪声具有非高斯性和频率随机性的问题,提出基于粒子滤波的深海采矿导航算法,并针对粒子滤波的粒子退化和贫化提出一种新的重采样算法。结合湖试数据,仿真实验表明新的重采样算法在获得更好的滤波精度的同时可以避免粒子贫化现象。最后,将基于改进的粒子滤波的深海采矿导航算法与基于无迹卡尔曼滤波算法的导航算法进行对比。结果表明本文提出的算法具有较高的精度和优良的鲁棒性。

Language英语
Citation statistics
Document Type期刊论文
Identifierhttp://ir.sia.cn/handle/173321/27322
Collection水下机器人研究室
Corresponding AuthorZhang ZH(张志慧); Zhang ZH(张志慧)
Affiliation1.State Key Laboratory of Robotics, Shenyang Institute of Automation,Chinese Academy of Sciences, Shenyang 110016, China
2.Institutes for Robotics and Intelligent Manufacturing,Chinese Academy of Sciences, Shenyang 110169, China
3.University of Chinese Academy of Sciences, Beijing 100049, China
4.State Key Laboratory of Robotics, Shenyang Institute of Automation,Chinese Academy of Sciences, Shenyang 110016, China
5.Institutes for Robotics and Intelligent Manufacturing,Chinese Academy of Sciences, Shenyang 110169, China
6.University of Chinese Academy of Sciences, Beijing 100049, China
Recommended Citation
GB/T 7714
Zhang ZH,Feng YB,Li ZG,et al. An underwater mining navigation method based on an improved particle filter[J]. 中国科学院大学学报,2020,37(4):507-515.
APA Zhang ZH.,Feng YB.,Li ZG.,Zhao XH.,Zhang ZH.,...&Zhao XH.(2020).An underwater mining navigation method based on an improved particle filter.中国科学院大学学报,37(4),507-515.
MLA Zhang ZH,et al."An underwater mining navigation method based on an improved particle filter".中国科学院大学学报 37.4(2020):507-515.
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