• DocumentCode
    1613335
  • Title

    Observable degree analysis for tracking

  • Author

    Xiao Yang ; Xinsheng Huang ; Shengjian Bai ; Qiang Fang ; Xiabin Dong

  • Author_Institution
    Coll. of Mechatron. Eng. & Autom., Nat. Univ. of Defense Technol., Changsha, China
  • fYear
    2013
  • Firstpage
    384
  • Lastpage
    387
  • Abstract
    An analysis of the observable degree of two tracking system is presented. It is shown that through the method based on mutual information, we can calculate the exact degree of observability of the system states and determine the estimation performance of the extended kalman filter(EKF) and particle filter(PF). Simulation results demonstrate the validity of the method.
  • Keywords
    Kalman filters; nonlinear filters; observability; particle filtering (numerical methods); state estimation; target tracking; EKF; PF; estimation performance; extended kalman filter; mutual information; observable degree analysis; particle filter; system states observability degree; tracking system; Eigenvalues and eigenfunctions; Estimation; Filtering theory; Information filters; Information theory; Observability; Bearing-only Tracking; Extended Kalman Filter(EKF); Information Theory; Observable Degree; Particle Filter(PF);
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Chinese Automation Congress (CAC), 2013
  • Conference_Location
    Changsha
  • Print_ISBN
    978-1-4799-0332-0
  • Type

    conf

  • DOI
    10.1109/CAC.2013.6775764
  • Filename
    6775764