• DocumentCode
    1637518
  • Title

    A Novel Unscented Kalman Filter in Autonomous Optical Navigation

  • Author

    Shulin, Sui ; Wenlong, Yao ; Lihong, Sun ; Jian, Yuan

  • Author_Institution
    Qingdao Univ. of Sci. & Technol., Qingdao
  • fYear
    2007
  • Firstpage
    462
  • Lastpage
    466
  • Abstract
    Through much research on unscented Kalman filter based on scaled and square-root algorithm in autonomous navigation, it is known that these algorithms take so much time on calculation. So an improved unscented Kalman filter algorithm is proposed in the paper for autonomous navigation to solve the non-real-time difficulty. Simple scheme is adopted to predigest the choose procedure of sigma-points and weights, which reduces a mass of complex operations. From both theory and practical simulation, it is shown that much mass of calculation is reduced when the dimension of state matrix is large, and not leads to bad filtering performance.
  • Keywords
    Kalman filters; matrix algebra; navigation; autonomous optical navigation; filtering performance; scaled algorithm; square-root algorithm; state matrix; unscented Kalman filter; Covariance matrix; Extraterrestrial measurements; Filtering; Gaussian distribution; Navigation; Noise measurement; Nonlinear equations; Optical control; Optical filters; State estimation; Autonomous optical navigation; SR-UKF; UKF;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control Conference, 2007. CCC 2007. Chinese
  • Conference_Location
    Hunan
  • Print_ISBN
    978-7-81124-055-9
  • Electronic_ISBN
    978-7-900719-22-5
  • Type

    conf

  • DOI
    10.1109/CHICC.2006.4346767
  • Filename
    4346767