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Proceedings Paper

Tracking multiple targets using a particle filter representation of the joint multitarget probability density
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Paper Abstract

This paper addresses the problem of tracking multiple moving targets by estimating their joint multitarget probability density (JMPD). The JMPD technique is a Bayesian method for tracking multiple targets that allows nonlinear, non-Gaussian target motions and measurement to state coupling. JMPD simultaneously estimates both the target states and the number of targets. In this paper, we give a new grid-free implementation of JMPD based on particle filtering techniques and explore several particle proposal strategies, resampling techniques, and particle diversification methods. We report the effect of these techniques on tracker performance in terms of tracks lost, mean squared error, and computational burden.

Paper Details

Date Published: 5 January 2004
PDF: 12 pages
Proc. SPIE 5204, Signal and Data Processing of Small Targets 2003, (5 January 2004); doi: 10.1117/12.502696
Show Author Affiliations
Chris M. Kreucher, Veridian Erim International Corp. (United States)
Keith D. Kastella, Veridian Erim International Corp. (United States)
Alfred O. Hero, Univ. of Michigan (United States)


Published in SPIE Proceedings Vol. 5204:
Signal and Data Processing of Small Targets 2003
Oliver E. Drummond, Editor(s)

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