• DocumentCode
    2012861
  • Title

    Research on Data Association in Three Passive Sensors Network

  • Author

    Hang, Liu ; Li-hua, Dou ; Feng, Pan ; Ling-xun, Dong

  • Author_Institution
    Beijing Inst. of Technol., Beijing
  • fYear
    2007
  • fDate
    May 30 2007-June 1 2007
  • Firstpage
    3235
  • Lastpage
    3238
  • Abstract
    In this paper, it is concerned with the static data association problem in the three distributed passive sensors network, in which each sensor can observe 2-dimensional angles (azimuth and elevation) of each target. A new fast data association approach is proposed in a multiple target dense environment with noise, missed detections, false alarm, and unknown number of the targets. Firstly, the data association of three sensors is transformed into the data association of two sensors about three groups, and the possible correct pairs of association are achieved by the statistic test. Secondly, the pairs of association which are detected by three sensors are got by the analysis method proposed in this paper, which is instead of m-D assignment. Lastly, the pairs of association which are detected by two sensors are got. The simulation results show that the proposed approach has higher association accuracy than the other conventional approaches.
  • Keywords
    sensor fusion; statistical testing; target tracking; distributed passive sensors network; multiple target dense environment; static data association problem; statistical testing; Automatic control; Automation; Azimuth; Gaussian noise; Information science; Military computing; Radar tracking; Statistical analysis; Testing; Working environment noise; data association; ghost; passive sensor;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control and Automation, 2007. ICCA 2007. IEEE International Conference on
  • Conference_Location
    Guangzhou
  • Print_ISBN
    978-1-4244-0817-7
  • Electronic_ISBN
    978-1-4244-0818-4
  • Type

    conf

  • DOI
    10.1109/ICCA.2007.4376960
  • Filename
    4376960