• DocumentCode
    2843852
  • Title

    Extended target tracking for high resolution sensor based ensemble Kalman filters

  • Author

    Xu, Jiahe ; Zhou, Yucheng ; Jing, Yuanwei

  • Author_Institution
    Dept. of Res. Inst. of Wood Ind., Chinese Acad. of Forestry, Beijing, China
  • fYear
    2010
  • fDate
    26-28 May 2010
  • Firstpage
    3308
  • Lastpage
    3313
  • Abstract
    The ensemble Kalman filter (EnKF) is developed to extended target tracking problem for high resolution sensors. The ensemble Kalman filter is based on an ellipsoidal model, which is proposed to exploit sensor measurement of target extent. The ellipsoidal model can provide extra information to enhance tracking accuracy, data association performance, and target identification. In contrast to the most commonly used extended Kalman filter (EKF), the EnKF provide more accurate and reliable estimation performance, due to the presence of high nonlinearity of the model. Correspondingly, the EnKF has lower computational complexity than the EKF. The EnKF is sensitive to uncertainty in the dynamic model, but much of the lost performance can be restored by treating the uncertainty as a random disturbance input. The developed EnKF algorithm on extended target tracking problem is validated and evaluated by computer simulations.
  • Keywords
    Kalman filters; sensors; target tracking; computational complexity; dynamic model; ellipsoidal model; ensemble Kalman filters; extended target tracking; high resolution sensor; sensor measurement; target identification; Filtering; Forestry; Infrared sensors; Kinematics; Radar tracking; Shape measurement; Spaceborne radar; State estimation; Target tracking; Uncertainty; ensemble Kalman filter (EnKF); extended target tracking; nonlinear filtering; uncertainty;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control and Decision Conference (CCDC), 2010 Chinese
  • Conference_Location
    Xuzhou
  • Print_ISBN
    978-1-4244-5181-4
  • Electronic_ISBN
    978-1-4244-5182-1
  • Type

    conf

  • DOI
    10.1109/CCDC.2010.5498595
  • Filename
    5498595