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Proceedings Paper

A new computational method for ambiguity assessment of solutions to assignment problems arising in target tracking
Author(s): Alexander D. Mont; Christopher P. Calderon; Aubrey B. Poore
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Paper Abstract

We present a new approach to estimating the probability of each association in a 2D assignment problem defined by likelihood ratios. Our method divides the set of feasible hypotheses into clusters, and converts a collection of hypotheses into a collection of clusters containing them, reducing the variance of the estimate. Simulations show that our method often generates substantially more accurate probability estimates in less time than traditional methods. Our method can obtain reasonably accurate probabilities of association based on only the input cost matrix and single best candidate solution, eliminating the need for a K-best solution method or MCMC sampling.

Paper Details

Date Published: 13 June 2014
PDF: 18 pages
Proc. SPIE 9092, Signal and Data Processing of Small Targets 2014, 90920J (13 June 2014); doi: 10.1117/12.2053400
Show Author Affiliations
Alexander D. Mont, Numerica Corp. (United States)
Christopher P. Calderon, Numerica Corp. (United States)
Aubrey B. Poore, Numerica Corp. (United States)

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

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