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Proceedings Paper

Evaluation of a posteriori probabilities of multi-frame data association hypotheses
Author(s): Shozo Mori; Chee Chong
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Paper Abstract

This paper discusses the problem of numerically evaluating multi-frame, data-association hypotheses in multiple-target tracking in terms of their a posteriori probabilities. We describe two approaches to the problem: (1) an approach based on K-best multi-frame data association hypothesis selection algorithms, and (2) a more direct approach to calculating a posteriori probabilities through Markov-chain-Monte-Carlo (MCMC) or sequential Monte Carlo (SMC) methods. This paper defines algorithms based on those two approaches and compares their performance, and it discusses their relative effectiveness, using simple numerical examples.

Paper Details

Date Published: 21 September 2007
PDF: 11 pages
Proc. SPIE 6699, Signal and Data Processing of Small Targets 2007, 66990L (21 September 2007); doi: 10.1117/12.734822
Show Author Affiliations
Shozo Mori, BAE Systems, Advanced Information Technologies (United States)
Chee Chong, BAE Systems, Advanced Information Technologies (United States)


Published in SPIE Proceedings Vol. 6699:
Signal and Data Processing of Small Targets 2007
Oliver E. Drummond; Richard D. Teichgraeber, Editor(s)

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