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Proceedings Paper

Particle filter tracking for long range radars
Author(s): Kevin Romeo; Peter Willett; Yaakov Bar-Shalom
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Paper Abstract

In this paper we present an approach for tracking in long range radar scenarios. We show that in these scenarios the extended Kalman filter is not desirable as it suffers from major consistency problems, and that particle filters may suffer from a loss of diversity among particles after resampling. This leads to sample impoverishment and the divergence of the filter. In the scenarios studied, this loss of diversity can be attributed to the very low process noise. However, a regularized particle filter and the Gaussian Mixture Sigma-Point Particle Filter are shown to avoid this diversity problem while producing consistent results.

Paper Details

Date Published: 15 May 2012
PDF: 13 pages
Proc. SPIE 8393, Signal and Data Processing of Small Targets 2012, 83930F (15 May 2012); doi: 10.1117/12.924336
Show Author Affiliations
Kevin Romeo, Univ. of Connecticut (United States)
Peter Willett, Univ. of Connecticut (United States)
Yaakov Bar-Shalom, Univ. of Connecticut (United States)


Published in SPIE Proceedings Vol. 8393:
Signal and Data Processing of Small Targets 2012
Oliver E. Drummond; Richard D. Teichgraeber, Editor(s)

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