Converted measurement Kalman filtering algorithm for radar target tracking

Chunling Yang; Quan-Zhan Zheng; Guo-Sui Liu

doi:10.1117/12.352884

15 July 1999 Converted measurement Kalman filtering algorithm for radar target tracking

Chunling Yang, Quan-Zhan Zheng, Guo-Sui Liu

Proceedings Volume 3692, Acquisition, Tracking, and Pointing XIII; (1999) https://doi.org/10.1117/12.352884
Event: AeroSense '99, 1999, Orlando, FL, United States

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.

Citation Download Citation

Chunling Yang, Quan-Zhan Zheng, and Guo-Sui Liu "Converted measurement Kalman filtering algorithm for radar target tracking", Proc. SPIE 3692, Acquisition, Tracking, and Pointing XIII, (15 July 1999); https://doi.org/10.1117/12.352884

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