The Impact of the Quality Assessment of Optimal Assignment for Data Association in a Multitarget Tracking Context

Dezert, J.; Tchamova, A.; Konstantinova, P.

doi:10.1515/cait-2015-0092

Abstract

The main purpose of this paper is to apply and to test the performance of a new method, based on belief functions, proposed by Dezert et al. in order to evaluate the quality of the individual association pairings provided in the optimal data association solution for improving the performances of multisensor-multitarget tracking systems. The advantages of its implementation in an illustrative realistic surveillance context, when some of the association decisions are unreliable and doubtful and lead to potentially critical mistake, are discussed. A comparison with the results obtained on the base of Generalized Data Association is made.

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The Impact of the Quality Assessment of Optimal Assignment for Data Association in a Multitarget Tracking Context

Abstract

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