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Proceedings Paper

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

In this paper we present an approach for tracking with a high-bandwidth active radar in long range scenarios with 3-D measurements in r-u-v coordinates. The 3-D low-process-noise scenarios considered are much more difficult than the ones we have previously investigated where measurements were in 2-D (i.e., polar coordinates). We show that in these 3-D scenarios the extended Kalman filter and its variants are not desirable as they suffer from either major consistency problems or degraded range accuracy, and most flavors of particle filter suffer from a loss of diversity among particles after resampling. This leads to sample impoverishment and 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 is shown to avoid this diversity problem while producing consistent results. The regularization is accomplished using a modified version of the Epanechnikov kernel.

Paper Details

Date Published: 13 June 2014
PDF: 15 pages
Proc. SPIE 9092, Signal and Data Processing of Small Targets 2014, 909209 (13 June 2014); doi: 10.1117/12.2050456
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. 9092:
Signal and Data Processing of Small Targets 2014
Oliver E. Drummond, Editor(s)

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