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13 June 2014 Particle filter for long range radar in RUV
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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.
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Kevin Romeo, Peter Willett, and Yaakov Bar-Shalom "Particle filter for long range radar in RUV", Proc. SPIE 9092, Signal and Data Processing of Small Targets 2014, 909209 (13 June 2014); https://doi.org/10.1117/12.2050456
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