• DocumentCode
    2838602
  • Title

    Research of improved probability data association algorithm for multi-target tracking

  • Author

    Zhengwang, Jia ; Yinya, Li ; Mingxiu, Mao ; Li, Chen ; Zhi, Guo

  • Author_Institution
    Sch. of Autom., Nanjing Univ. of Sci. & Technol., Nanjing, China
  • fYear
    2009
  • fDate
    17-19 June 2009
  • Firstpage
    4919
  • Lastpage
    4923
  • Abstract
    An improved probabilistic data association is proposed to overcome both the drawback of complication in joint probabilistic data association and the unneutrality of multi-targets processing by probabilistic data association. It incorporates the radar Doppler measurement information and modifies weighting of state estimation of measurements in the common region, and then makes the final estimation more exact and improves further performance. The theoretical analysis and Monte-Carlo simulation results show that the algorithm has small computation cost and a better real-time tracking performance.
  • Keywords
    Doppler radar; Monte Carlo methods; sensor fusion; target tracking; Monte-Carlo simulation; multitarget tracking; multitargets processing; probabilistic data association; probability data association algorithm; radar Doppler measurement information; real-time tracking performance; state estimation; Algorithm design and analysis; Automation; Computational efficiency; Doppler measurements; Doppler radar; Performance analysis; Radar measurements; Radar tracking; State estimation; Data association; Multi-target tracking; Probabilistic data association algorithm;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control and Decision Conference, 2009. CCDC '09. Chinese
  • Conference_Location
    Guilin
  • Print_ISBN
    978-1-4244-2722-2
  • Electronic_ISBN
    978-1-4244-2723-9
  • Type

    conf

  • DOI
    10.1109/CCDC.2009.5194908
  • Filename
    5194908