Fuzzy multicriteria decision making in the assignment problem

Elana Dror-Rein; Harvey B. Mitchell

doi:10.1117/12.279535

29 October 1997 Fuzzy multicriteria decision making in the assignment problem

Elana Dror-Rein, Harvey B. Mitchell

Proceedings Volume 3163, Signal and Data Processing of Small Targets 1997; (1997) https://doi.org/10.1117/12.279535
Event: Optical Science, Engineering and Instrumentation '97, 1997, San Diego, CA, United States

Abstract

Many multi-target tracking systems work by continually updating the target tracks on the basis of received target measurements. This involves solving the assignment problem, i.e. finding the maximum set of track-to-measurement associations with the largest overall likelihood. To minimize the number of association errors, it is traditional to include targets for which there are no corresponding tracks and tracks for which there are no corresponding measurements. These missing tracks and missing measurements are taken into account by augmenting the track-to-measurement likelihood matrix. In this paper, we present a new approach to solving the assignment problem which does not involve augmenting the likelihood matrix. The solution found in the new approach contains n* high-quality track-to-measurement associations. This set of n* associations optimally satisfies two criteria: (1) a high average likelihood and (2) n* close to the expected number of true track-to-measurement associations. Thus, the number of track-to- measurement associations, n*, is not specified beforehand but rather is an output of the algorithm. The two criteria are defined by fuzzy membership functions, and the solution is found using a fuzzy multi-criteria decision-making algorithm.

Citation Download Citation

Elana Dror-Rein and Harvey B. Mitchell "Fuzzy multicriteria decision making in the assignment problem", Proc. SPIE 3163, Signal and Data Processing of Small Targets 1997, (29 October 1997); https://doi.org/10.1117/12.279535

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