• DocumentCode
    941
  • Title

    Modified Murty's Algorithm for Diverse Multitarget Top Hypothesis Extraction

  • Author

    Xiaofan He ; Tharmarasa, Ratnasingham ; Kirubarajan, Thiagalingam ; Pelletier, M.

  • Author_Institution
    Dept. of Electr. & Comput. Eng., McMaster Univ., Hamilton, ON, Canada
  • Volume
    49
  • Issue
    1
  • fYear
    2013
  • fDate
    Jan. 2013
  • Firstpage
    602
  • Lastpage
    610
  • Abstract
    In most multiple hypothesis tracking (MHT) implementations, the data association is solved using Murty´s algorithm. However, since Murty´s algorithm has no control over the diversity of measurement-to-track associations, often, the top associations vary only slightly. To overcome this problem and to provide more flexibility in the selection of hypotheses, a modified Murty´s algorithm, which can achieve any user-defined (or adaptable) diversity of association of different types of tracks, is proposed.
  • Keywords
    sensor fusion; target tracking; Murty algorithm; data association; diverse multitarget top hypothesis extraction; hypothesis selection; measurement-to-track association; Algorithm design and analysis; Clutter; Current measurement; Nickel; Partitioning algorithms; Standards; Target tracking;
  • fLanguage
    English
  • Journal_Title
    Aerospace and Electronic Systems, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9251
  • Type

    jour

  • DOI
    10.1109/TAES.2013.6404123
  • Filename
    6404123
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=941