• DocumentCode
    2038699
  • Title

    Improvement of UKF Algorithm and Robustness Study

  • Author

    Mou Zhong-Kai ; Sui Li-Fen

  • Author_Institution
    Inst. of Survey & Mapping, Inf. Eng. Univ., Zhengzhou
  • fYear
    2009
  • fDate
    23-24 May 2009
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    Iterated unscented Kalman filter (IUKF) algorithm has improved the unscented Kalman filter (UKF) and enhanced the performance of filter estimation by using Newton-Raphson iterative equation. This paper improves IUKF algorithm ulteriorly after detailedly analyzing principle of IUKF and its iterative equation, and proposes a new filtering algorithm with robustness-Improved IUKF. Then the performance of the new algorithm is validated by two experiments. The results show that the improved IUKF is more robust which can effectively resist the influence of measurement outlier.
  • Keywords
    Kalman filters; Newton-Raphson method; Newton-Raphson iterative equation; UKF algorithm; measurement outlier; unscented Kalman filter; Density measurement; Equations; Filtering algorithms; Filters; Iterative algorithms; Linear approximation; Resists; Robustness; State estimation; Taylor series;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Systems and Applications, 2009. ISA 2009. International Workshop on
  • Conference_Location
    Wuhan
  • Print_ISBN
    978-1-4244-3893-8
  • Electronic_ISBN
    978-1-4244-3894-5
  • Type

    conf

  • DOI
    10.1109/IWISA.2009.5072908
  • Filename
    5072908