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Proceedings Paper

Converted measurement Kalman filtering algorithm for radar target tracking
Author(s): Chunling Yang; Quan-Zhan Zheng; Guo-Sui Liu
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Paper Abstract

In this article, the filtering-algorithm for target tracking is studied in nonlinear systems. First, the converted measurement Kalman filtering algorithm (CMKFA) is inferred in 3D space. The statistics of the errors in converted measurements conditioned on target's true position is obtained, and the statistics of the errors in converted measurements conditioned on measurement is given to. Then it is proved that the CMKF is a linear unbiased least mean square estimator of debiased converted measurements under certain conditions. Finally, from simulations, it is proved that CMKF has a higher target tracking accuracy than EKF.

Paper Details

Date Published: 15 July 1999
PDF: 8 pages
Proc. SPIE 3692, Acquisition, Tracking, and Pointing XIII, (15 July 1999); doi: 10.1117/12.352884
Show Author Affiliations
Chunling Yang, Nanjing Univ. of Science and Technology (China)
Quan-Zhan Zheng, Nanjing Univ. of Science and Technology (China)
Guo-Sui Liu, Nanjing Univ. of Science and Technology (China)


Published in SPIE Proceedings Vol. 3692:
Acquisition, Tracking, and Pointing XIII
Michael K. Masten; Larry A. Stockum, Editor(s)

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