• DocumentCode
    3414019
  • Title

    Application of Robust Kalman Filtering to Integrated Navigation Based on Inertial Navigation System and Dead Reckoning

  • Author

    Dai, Hu ; Li, Jianxun ; Jin, Huiming

  • Author_Institution
    Dept. of Autom., Shanghai Jiaotong Univ., Shanghai, China
  • Volume
    2
  • fYear
    2010
  • fDate
    23-24 Oct. 2010
  • Firstpage
    189
  • Lastpage
    193
  • Abstract
    Aiming at solving the problem that the integrated navigation system which consists of inertial navigation system (INS) and dead reckoning (DR) has outliers and disturbance in measurement, as well as uncertainty in modeling, this paper proposes a new data processing method based on the technology of robust Kalman filtering (KF). The robust estimation is adopted to eliminate the outliers of the measurement of the sensors, thus the navigation information can be available for INS and DR respectively. Then for the INS/DR integrated navigation, the robust filtering is applied to resolve the modeling uncertainty. With this proposed method, experimental results show that the effect of the outliers in the measurement is eliminated, meanwhile, the robustness of the system is guaranteed, and therefore, the accuracy of integrated navigation is ensured.
  • Keywords
    Kalman filters; inertial navigation; INS-DR integrated navigation system; data processing method; dead reckoning; inertial navigation system; robust Kalman filtering; robust estimation; sensor measurement; Filtering; Global Positioning System; Mathematical model; Measurement uncertainty; Position measurement; Robustness; DR; INS; integrated navigation system; robust estimation; robust filtering;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Artificial Intelligence and Computational Intelligence (AICI), 2010 International Conference on
  • Conference_Location
    Sanya
  • Print_ISBN
    978-1-4244-8432-4
  • Type

    conf

  • DOI
    10.1109/AICI.2010.162
  • Filename
    5656442