• DocumentCode
    85187
  • Title

    Kalman and smooth variable structure filters for robust estimation

  • Author

    Gadsden, Stephen Andrew ; Habibi, Saeid ; Kirubarajan, Thia

  • Author_Institution
    Mech. Eng., McMaster Univ., Hamilton, ON, Canada
  • Volume
    50
  • Issue
    2
  • fYear
    2014
  • fDate
    Apr-14
  • Firstpage
    1038
  • Lastpage
    1050
  • Abstract
    The extended Kalman filter (EKF) and the unscented Kalman filter (UKF) are among the most popular estimation methods. The smooth variable structure filter (SVSF) is a relatively new sliding mode estimator. In an effort to use the accuracy of the EKF and the UKF and the robustness of the SVSF, the filters have been combined, resulting in two new estimation strategies, called the EK-SVSF and the UK-SVSF, respectively. The algorithms were validated by testing them on a well-known target tracking computer experiment.
  • Keywords
    Kalman filters; estimation theory; nonlinear filters; target tracking; variable structure systems; EKF; SVSF; UKF; extended Kalman filter; robust estimation; sliding mode estimator; smooth variable structure filters; target tracking; unscented Kalman filter; Equations; Estimation; Kalman filters; Mathematical model; Nonlinear systems; Robustness; Smoothing methods;
  • fLanguage
    English
  • Journal_Title
    Aerospace and Electronic Systems, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9251
  • Type

    jour

  • DOI
    10.1109/TAES.2014.110768
  • Filename
    6850138