Paper
15 May 2012 Particle filter tracking for long range radars
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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.
© (2012) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
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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CITATIONS
Cited by 6 scholarly publications.
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KEYWORDS
Particles

Particle filters

Detection and tracking algorithms

Radar

Filtering (signal processing)

Gaussian filters

Digital filtering

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