• DocumentCode
    233770
  • Title

    An improved method of adaptive Kalman filtering for vehicular kinematic positioning

  • Author

    Wang Meng ; Hu Huaen ; Wang Xiaofeng ; Zhang He ; Zhang Aijun

  • Author_Institution
    Sch. of Mech. Eng., Nanjing Univ. of Sci. & Technol., Nanjing, China
  • fYear
    2014
  • fDate
    28-30 July 2014
  • Firstpage
    782
  • Lastpage
    786
  • Abstract
    Due to the fact that the traditional Kalman filtering has difficulties in determining dynamic noise and observation noise in the application of vehicular GPS dynamic positioning, an improved adaptive Kalman filter algorithm is put forward for GPS dynamic positioning in this paper. The proposed algorithm has the ability of making a real-time correction on the parameters of system noise, avoiding the filter divergence during the traditional Kalman filtering. In addition, it overcomes the problems caused by the variable dimensions of the system positioning state. Experiment results have demonstrated the outstanding adaptive ability of the improved Kalman filter.
  • Keywords
    Global Positioning System; Kalman filters; adaptive filters; adaptive Kalman filter algorithm; dynamic noise; filter divergence; observation noise; real-time correction; traditional Kalman filtering; vehicular GPS dynamic positioning; vehicular kinematic positioning; Global Positioning System; Heuristic algorithms; Kalman filters; Mathematical model; Noise; Vehicle dynamics; Adaptive; GPS; Kalman Filtering; Vehicular;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control Conference (CCC), 2014 33rd Chinese
  • Conference_Location
    Nanjing
  • Type

    conf

  • DOI
    10.1109/ChiCC.2014.6896726
  • Filename
    6896726