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Proceedings Paper

Finite resolution multitarget tracking
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Paper Abstract

Target tracking algorithms have to operate in an environment of uncertain measurement origin, due to the presence of randomly detected target measurements as well as clutter measurements from unwanted random scatterers. A majority of Bayesian multi-target tracking algorithms suffer from computational complexity which is exponential in the number of tracks and the number of shared measurements. The Linear Multi-target (LM) tracking procedure is a Bayesian multi-target tracking approximation with complexity which is linear in the number of tracks and the number of shared measurements. It also has a much simpler structure than the "optimal" Bayesian multi-target tracking, with apparently negligible decrease in performance. A vast majority of target tracking algorithms have been developed with the assumption of infinite sensor resolution, where a measurement can have only one source. This assumption is not valid for real sensors, such as radars. This paper presents a multi-target tracking algorithm which removes this restriction. The procedure utilizes a simple structure of LM tracking procedure to obtain a LM Finite Resolution (LMfr) tracking procedure which is much simpler than the previously published efforts. Instead of calculating the probability of measurement merging for each combination of potentially merging targets, we evaluate only one merging hypotheses for each measurement and each track. A simulation study is presented which compares LMfr-IPDA with LM-IPDA and IPDA target tracking in a cluttered environment utilizing a finite resolution sensor with five crossing targets. The study concentrates on the false track discrimination performance and the track retention capabilities.

Paper Details

Date Published: 14 September 2005
PDF: 12 pages
Proc. SPIE 5913, Signal and Data Processing of Small Targets 2005, 59130K (14 September 2005); doi: 10.1117/12.617094
Show Author Affiliations
Darko Mušicki, Univ. of Melbourne (Australia)
Mark R. Morelande, Univ. of Melbourne (Australia)

Published in SPIE Proceedings Vol. 5913:
Signal and Data Processing of Small Targets 2005
Oliver E. Drummond, Editor(s)

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