Particle filter tracking for long range radars

Kevin Romeo; Peter Willett; Yaakov Bar-Shalom

doi:10.1117/12.924336

15 May 2012 Particle filter tracking for long range radars

Kevin Romeo, Peter Willett, Yaakov Bar-Shalom

Proceedings Volume 8393, Signal and Data Processing of Small Targets 2012; 83930F (2012) https://doi.org/10.1117/12.924336
Event: SPIE Defense, Security, and Sensing, 2012, Baltimore, Maryland, United States

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.

Citation Download Citation

Kevin Romeo, Peter Willett, and Yaakov Bar-Shalom "Particle filter tracking for long range radars", Proc. SPIE 8393, Signal and Data Processing of Small Targets 2012, 83930F (15 May 2012); https://doi.org/10.1117/12.924336

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