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Greedy and $K$-Greedy Algorithms for Multidimensional Data Association

Federico Perea,H. D. Waard

Published 2011 in IEEE Transactions on Aerospace and Electronic Systems

ABSTRACT

The multidimensional assignment (MDA) problem is a combinatorial optimization problem arising in many applications, for instance multitarget tracking (MTT). The objective of an MDA problem of dimension d ∈ N is to match groups of d objects in such a way that each measurement is associated with at most one track and each track is associated with at most one measurement from each list, optimizing a certain objective function. It is well known that the MDA problem is NP-hard for d ≥ 3. In this paper five new polynomial time heuristics to solve the MDA problem arising in MTT are presented. They are all based on the semi-greedy approach introduced in earlier research. Experimental results on the accuracy and speed of the proposed algorithms in MTT problems are provided.

PUBLICATION RECORD

  • Publication year

    2011

  • Venue

    IEEE Transactions on Aerospace and Electronic Systems

  • Publication date

    2011-07-05

  • Fields of study

    Mathematics, Computer Science

  • Identifiers
    DOI 10.1109/TAES.2011.5937273
  • External record

    Open on Semantic Scholar

  • Source metadata

    Semantic Scholar

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