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题名:
The Unscented Kalman Filter for State Estimation of 3-Dimension Bearing-Only Tracking
作者: Wan-ping Wang; Sheng Liao; Ting-wen Xing
刊名: Information Engineering and computer Science
出版日期: 2009
卷号: 138-142
通讯作者: Wan-ping Wang
文章类型: 期刊论文
中文摘要: The unscented Kalman filter (UKF) is presented as an alternative of extend Kalman filter (EKF) for bearing-only tracking. Compared with EKF, UKF has a better performance that estimation precision does not depend on state initialization error. In the same noise angle measurement data, UKF has better precision. UKF can be used to have a good estimation at large state initialization error. Simulation experiments are present and show that UKF is used for better state estimation result in 3-dimension bearing-only tracking.
英文摘要: The unscented Kalman filter (UKF) is presented as an alternative of extend Kalman filter (EKF) for bearing-only tracking. Compared with EKF, UKF has a better performance that estimation precision does not depend on state initialization error. In the same noise angle measurement data, UKF has better precision. UKF can be used to have a good estimation at large state initialization error. Simulation experiments are present and show that UKF is used for better state estimation result in 3-dimension bearing-only tracking.
收录类别: Ei
语种: 英语
内容类型: 期刊论文
URI标识: http://ir.ioe.ac.cn/handle/181551/4196
Appears in Collections:应用光学研究室(二室)_期刊论文

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作者单位: 中国科学院光电技术研究所

Recommended Citation:
Wan-ping Wang,Sheng Liao,Ting-wen Xing. The Unscented Kalman Filter for State Estimation of 3-Dimension Bearing-Only Tracking[J]. Information Engineering and computer Science,2009,138-142.
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