Use of the radial velocity measurement in target tracking

Jianguo Wang; Peikun He; Teng Long

doi:10.1109/TAES.2003.1207253

Use of the radial velocity measurement in target tracking

Jianguo Wang^*, Peikun He, Teng Long

^*此作品的通讯作者

信息与电子学院

Beijing Institute of Technology

科研成果: 期刊稿件 › 文章 › 同行评审

53 引用（Scopus）

摘要

A new sequential filtering algorithm that incorporates the radial velocity measurement into Kalman filter in the presence of correlated range and radial velocity measurement errors is presented. An analysis is given about its asymptotic behavior on the basis of the analysis of the stochastic controllability and observability. The simulation results verify the analysis and show that the new algorithm is superior to the conventional extended Kalman filter (EKF) and close to an ideal filter.

源语言	英语
页（从-至）	401-413
页数	13
期刊	IEEE Transactions on Aerospace and Electronic Systems
卷	39
期	2
DOI	https://doi.org/10.1109/TAES.2003.1207253
出版状态	已出版 - 4月 2003

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10.1109/TAES.2003.1207253

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Wang, J., He, P., & Long, T. (2003). Use of the radial velocity measurement in target tracking. IEEE Transactions on Aerospace and Electronic Systems, 39(2), 401-413. https://doi.org/10.1109/TAES.2003.1207253

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abstract = "A new sequential filtering algorithm that incorporates the radial velocity measurement into Kalman filter in the presence of correlated range and radial velocity measurement errors is presented. An analysis is given about its asymptotic behavior on the basis of the analysis of the stochastic controllability and observability. The simulation results verify the analysis and show that the new algorithm is superior to the conventional extended Kalman filter (EKF) and close to an ideal filter.",

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AB - A new sequential filtering algorithm that incorporates the radial velocity measurement into Kalman filter in the presence of correlated range and radial velocity measurement errors is presented. An analysis is given about its asymptotic behavior on the basis of the analysis of the stochastic controllability and observability. The simulation results verify the analysis and show that the new algorithm is superior to the conventional extended Kalman filter (EKF) and close to an ideal filter.

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Use of the radial velocity measurement in target tracking

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