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An adaptive square-root unscented Kalman filter for underwater Vehicle navigation
Lin YP(林燕平); Liu KZ(刘开周); Wang XL(王秀莲)
作者部门水下机器人研究室
会议名称11th IEEE International Conference on Mechatronics and Automation, IEEE ICMA 2014
会议日期August 3-6, 2014
会议地点Tianjin, China
会议录名称2014 IEEE International Conference on Mechatronics and Automation, IEEE ICMA 2014
出版者IEEE Computer Society
出版地Washington, DC
2014
页码717-722
收录类别EI ; CPCI(ISTP)
EI收录号20143818167253
WOS记录号WOS:000366848100124
产权排序1
ISBN号978-1-4799-3978-7
关键词Mechanical Engineering Mechatronics
摘要In order to increase the approximation accuracy of the state estimate of nonlinear systems and to guarantee numerical stability of the unscented Kalman filter (UKF), a novel adaptive square-root unscented Kalman filter (ASRUKF) based on modified Sage-Husa noise statistics estimator is proposed. The new adaptive filter method with adaptability to statistical characteristic of noise is able to compensate the lack of a priori knowledge of the system's noise statistics. A six-degree-of-freedom dynamic model is introduced to denote the motion model of Human Occupied Vehicle (HOV) in the water, while the adaptive SRUKF is employed for off-line estimation of the state of HOV. Tests are conducted with respect to the data obtained from previous sea trial, and the results are compared with those obtained by normal UKF and SRUKF to indicate its effectiveness and improvements. © 2014 IEEE.
语种英语
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文献类型会议论文
条目标识符http://ir.sia.cn/handle/173321/15149
专题水下机器人研究室
通讯作者Lin YP(林燕平)
作者单位1.School of Information Science and Engineering, Shenyang Ligong University, Shenyang, Liaoning Province, China
2.State Key Laboratory of Robotics, Shenyang Institute of Automation, Shenyang, Liaoning Province, China
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GB/T 7714
Lin YP,Liu KZ,Wang XL. An adaptive square-root unscented Kalman filter for underwater Vehicle navigation[C]. Washington, DC:IEEE Computer Society,2014:717-722.
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