• DocumentCode
    1690673
  • Title

    Efficient particle filters for tracking manoeuvring targets in clutter

  • Author

    Doucet, Arnaud ; Gordon, Neil

  • Author_Institution
    Signal Process. Group, Cambridge Univ., UK
  • fYear
    1999
  • fDate
    6/21/1905 12:00:00 AM
  • Firstpage
    42461
  • Lastpage
    42465
  • Abstract
    In this paper, we propose an on-line Monte Carlo (MC) filtering algorithm to perform optimal state estimation for Jump Markov Linear Systems (JMLS). The approach taken is loosely based on the bootstrap filter which, whilst being a powerful general algorithm in its original form, does not make the most of the structure of JMLS. The proposed algorithm exploits this structure and is demonstrated to provide a performance improvement over the IMM-PDA for tracking manoeuvring targets in clutter
  • Keywords
    tracking filters; Kalman filters; bootstrap filter; clutter; efficient particle filters; false measurements; jump Markov linear systems; manoeuvring target tracking; on-line Monte Carlo filtering algorithm; optimal state estimation; simulation-based filter; statistical model; true measurements;
  • fLanguage
    English
  • Publisher
    iet
  • Conference_Titel
    Target Tracking: Algorithms and Applications (Ref. No. 1999/090, 1999/215), IEE Colloquium on
  • Conference_Location
    London
  • Type

    conf

  • DOI
    10.1049/ic:19990505
  • Filename
    827250