• DocumentCode
    233776
  • Title

    An adaptive UKF algorithm and its application for vehicle integrated navigation system

  • Author

    Wu Xiao-yan ; Song Chun-lei ; Chen Jia-bin ; Han Yong-qiang

  • Author_Institution
    Sch. of Autom., Beijing Inst. of Technol., Beijing, China
  • fYear
    2014
  • fDate
    28-30 July 2014
  • Firstpage
    787
  • Lastpage
    791
  • Abstract
    In order to overcome the problems existing in Kalman filter(KF), extended Kalman filter(EKF) and unscented Kalman filter(UKF) in the vehicle integrated navigation system, a method is adopted to solve this problem. UKF algorithm is introduced, and an improved UKF was presented which is an adapted factor is introduced in UKF. It is shown, in vehicle integrated navigation system, UKF is superior to the EKF, AUKF is better than UKF, AUKF has better in reducing sensitivity of the process and the initial value of the statistical characteristics of the noise and the accuracy, reliability of the navigation solution.
  • Keywords
    Kalman filters; aerospace control; inertial navigation; nonlinear filters; path planning; adaptive UKF algorithm; extended Kalman filter; statistical characteristics; unscented Kalman filter; vehicle integrated navigation system; Accuracy; Equations; Kalman filters; Mathematical model; Navigation; Noise; adapted factor; extended Kalman filter; unscented Kalman filter; vehicle navigation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control Conference (CCC), 2014 33rd Chinese
  • Conference_Location
    Nanjing
  • Type

    conf

  • DOI
    10.1109/ChiCC.2014.6896727
  • Filename
    6896727