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

Chris M. Kreucher; Keith D. Kastella; Alfred O. Hero III

doi:10.1117/12.502696

5 January 2004 Tracking multiple targets using a particle filter representation of the joint multitarget probability density

Chris M. Kreucher, Keith D. Kastella, Alfred O. Hero III

Author Affiliations +

Proceedings Volume 5204, Signal and Data Processing of Small Targets 2003; (2004) https://doi.org/10.1117/12.502696
Event: Optical Science and Technology, SPIE's 48th Annual Meeting, 2003, San Diego, California, United States

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.

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Chris M. Kreucher, Keith D. Kastella, and Alfred O. Hero III "Tracking multiple targets using a particle filter representation of the joint multitarget probability density", Proc. SPIE 5204, Signal and Data Processing of Small Targets 2003, (5 January 2004); https://doi.org/10.1117/12.502696

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