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

^*Corresponding author for this work

School of Information and Electronics

Beijing Institute of Technology

Research output: Contribution to journal › Article › peer-review

53 Citations (Scopus)

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.

Original language	English
Pages (from-to)	401-413
Number of pages	13
Journal	IEEE Transactions on Aerospace and Electronic Systems
Volume	39
Issue number	2
DOIs	https://doi.org/10.1109/TAES.2003.1207253
Publication status	Published - Apr 2003

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10.1109/TAES.2003.1207253

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title = "Use of the radial velocity measurement in target tracking",

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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AU - Wang, Jianguo

AU - He, Peikun

AU - Long, Teng

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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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JO - IEEE Transactions on Aerospace and Electronic Systems

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Use of the radial velocity measurement in target tracking

Abstract

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