• DocumentCode
    2887979
  • Title

    Improvement of multisensor data fusion on track loss in clutter

  • Author

    Ningzhou, Cui ; Weixin, Xie ; Yu Xiongnan ; Yuanliang, Ma

  • Author_Institution
    Dept. of Electron. Eng., Xidian Univ., Xi´´an, China
  • fYear
    1996
  • fDate
    8-10 Oct 1996
  • Firstpage
    719
  • Lastpage
    722
  • Abstract
    Improvement of multisensor data fusion on track loss in clutter is studied analytically in this paper. Calculating the transition probability density function of the fusion prediction error, the authors have analyzed the dependence of the fusion track loss statistics, such as mean time to lose track and cumulative probability of having lost track, on the clutter spatial density for nearest-neighbor association. The results show that multisensor data fusion can improve the tracking performance in clutter with low track loss probability
  • Keywords
    probability; radar clutter; radar tracking; sensor fusion; target tracking; clutter spatial density; fusion prediction error; fusion track loss statistics; multisensor data fusion; nearest-neighbor association; radar clutter; track loss probability; tracking performance; transition probability density function; Covariance matrix; Filters; Gaussian noise; Neural networks; Probability; Sensor fusion; State estimation; Target tracking; Technological innovation; White noise;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Radar, 1996. Proceedings., CIE International Conference of
  • Conference_Location
    Beijing
  • Print_ISBN
    0-7803-2914-7
  • Type

    conf

  • DOI
    10.1109/ICR.1996.574592
  • Filename
    574592