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Volume 26 Issue 5
 
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Article Navigation >  Journal of Unmanned Undersea Systems  > 2018  >  26(5): 444-448
ZHAO Wei-kang, HAN Yi-na, ZHANG Hao-yu, YANG Yi-xin, LIU Qing-yu. An Improved Hungarian Algorithm for Multiple Hypothesis Tracking[J]. Journal of Unmanned Undersea Systems, 2018, 26(5): 444-448. doi: 10.11993/j.issn.2096-3920.2018.05.011
Citation: ZHAO Wei-kang, HAN Yi-na, ZHANG Hao-yu, YANG Yi-xin, LIU Qing-yu. An Improved Hungarian Algorithm for Multiple Hypothesis Tracking[J]. Journal of Unmanned Undersea Systems, 2018, 26(5): 444-448. doi: 10.11993/j.issn.2096-3920.2018.05.011
shu

An Improved Hungarian Algorithm for Multiple Hypothesis Tracking

doi: 10.11993/j.issn.2096-3920.2018.05.011
  • 1.

    School of Marine and Technology, Northwestern Polytechnical University, Xi’an 710072, China

  • 2.

    Naval Research Academy, Beijing 100073, China

  • Received Date: 2016-11-19
  • Rev Recd Date: 2016-12-18
  • Publish Date: 2018-10-31
    Abstract
  • Hungarian algorithm is a core algorithm in multiple hypothesis tracking technology, and it takes up most of the computation time in multiple hypothesis tracking(MHT). Considering that the assignment problem in the MHT has particularity, i.e., the efficiency matrix is sparse, this paper proposes a method for reducing the dimension of the efficiency matrix, and the computation flow is given. Comparison of the time consumption between the proposed method and traditional Hungarian algorithm in dealing with larger efficiency matrix shows that the proposed method greatly reduces the amount of computation while ensuring consistency with the results of the Hungarian algorithm.

     

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