• DocumentCode
    159048
  • Title

    Belief rule-based methodology and Particle filter for radar target tracking

  • Author

    Wei Liu ; Xianqiao Chen ; Xiumin Chu

  • Author_Institution
    Sch. of Comput. Sci. & Technol., Wuhan Univ. of Technol., Wuhan, China
  • fYear
    2014
  • fDate
    9-10 Oct. 2014
  • Firstpage
    85
  • Lastpage
    90
  • Abstract
    With the rapid development of information technology in inland waterway, radar was widely used to track the ship running, in order to ensure the safe and efficient shipping industry development, as well as to avoid a ship collision causing unnecessary economic losses. For the problem of radar target tracking data associated, a method of data association with radar data was proposed, which was based on radar target course and speed. By this method, the target error or loss problem was solved when the target density was large and used belief rule-based (BRB) methodology to verify the reliability of this method. Real target points obtained by this method had been filtered through particle filter. And then the radar target tracking was achieved. This method has a good target tracking results, verified by Monte Carlo simulations.
  • Keywords
    Monte Carlo methods; belief networks; object tracking; particle filtering (numerical methods); radar tracking; rivers; sensor fusion; ships; transportation; BRB methodology; Monte Carlo simulations; belief rule-based methodology; data association; economic losses; inland waterway; particle filter; radar target course; radar target speed; radar target tracking; ship collision; ship tracking; shipping industry development; Marine vehicles; Noise; Particle filters; Radar tracking; Target tracking; Vectors; BRB; particle filter; radar target tracking;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Informative and Cybernetics for Computational Social Systems (ICCSS), 2014 International Conference on
  • Conference_Location
    Qingdao
  • Print_ISBN
    978-1-4799-4753-9
  • Type

    conf

  • DOI
    10.1109/ICCSS.2014.6961821
  • Filename
    6961821