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Proceedings Paper

Approximate calculation of marginal association probabilities using a hybrid data association model
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Paper Abstract

The calculation of marginal association probabilities is the major computational bottleneck in the Joint Probabilistic Data Association Filter (JPDAF). In this paper, we investigate approximations for the marginal associations that simplify the (computational complex) original association model in order to obtain efficient algorithms. In this context, we first discuss the Bakhtiar-Alavi algorithm and the Linear Multitarget Integrated Probabilistic Data Association (LMIPDA) algorithm. Second, we propose a fast novel approximation that exploits systematic combinations of the JPDAF measurement model with the Probabilistic Multi-Hypothesis Tracker (PMHT) measurement model. The discussed methods are evaluated by means of a tracking scenario with a high number of closely-spaced targets.

Paper Details

Date Published: 13 June 2014
PDF: 8 pages
Proc. SPIE 9092, Signal and Data Processing of Small Targets 2014, 90920L (13 June 2014); doi: 10.1117/12.2053431
Show Author Affiliations
Marcus Baum, Univ. of Connecticut (United States)
Peter Willett, Univ. of Connecticut (United States)
Yaakov Bar-Shalom, Univ. of Connecticut (United States)
Uwe D. Hanebeck, Karlsruhe Institute of Technology (Germany)

Published in SPIE Proceedings Vol. 9092:
Signal and Data Processing of Small Targets 2014
Oliver E. Drummond, Editor(s)

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