• DocumentCode
    2721863
  • Title

    Joint Sigma-Point Kalman Filter Based Bearing-Only Tracking

  • Author

    Hou, Daiwen ; Yin, Fuliang ; Zhang, Liyan

  • Author_Institution
    Sch. of Electron. & Inf. Eng., Dalian Univ. of Technol.
  • Volume
    1
  • fYear
    0
  • fDate
    0-0 0
  • Firstpage
    944
  • Lastpage
    948
  • Abstract
    A novel joint sigma-point Kalman filter algorithm is proposed to solve the problems of slow convergence rate and biased state estimation when systematic error exists in bearing-only target tracking. The algorithm can eliminate the effect of systematic error to the state estimation as well as reduce linearization error. The simulation results demonstrate the validity of the proposed algorithm
  • Keywords
    Kalman filters; state estimation; target tracking; tracking filters; bearing-only target tracking; joint sigma-point Kalman filter based bearing-only tracking; linearization error reduction; sigma-point transformation; state estimation; Acoustic measurements; Convergence; Electromagnetic measurements; Electromagnetic radiation; Filtering; Filters; Noise measurement; Radar tracking; State estimation; Target tracking; Bearing-only tracking; Kalman filter; sigma-point transformation; systematic error;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Control and Automation, 2006. WCICA 2006. The Sixth World Congress on
  • Conference_Location
    Dalian
  • Print_ISBN
    1-4244-0332-4
  • Type

    conf

  • DOI
    10.1109/WCICA.2006.1712483
  • Filename
    1712483
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2721863