• DocumentCode
    1082006
  • Title

    Detection of satellite attitude sensor faults using the UKF

  • Author

    Xiong, K. ; Chan, C.W. ; Zhang, H.Y.

  • Author_Institution
    Beihang Univ., Beijing
  • Volume
    43
  • Issue
    2
  • fYear
    2007
  • fDate
    4/1/2007 12:00:00 AM
  • Firstpage
    480
  • Lastpage
    491
  • Abstract
    A novel fault detection (FD) method for nonlinear systems using the residuals generated by the unscented Kalman filter (UKF) is proposed. The errors of the UKF are derived and sufficient conditions for the convergence of the UKF are presented. As the local approach is a powerful statistical technique for detecting changes in the mean of a Gaussian process, it is used to devise a hypothesis test to detect faults from residuals obtained from the UKF. Further, it is demonstrated that the selection of a sample number is important in improving the performance of the local approach. To illustrate the implementation and performance of the proposed technique, it is applied to detect sensor faults in the measurement of satellite attitude.
  • Keywords
    Gaussian processes; Kalman filters; artificial satellites; attitude measurement; fault diagnosis; sensors; Gaussian process; UKF; fault detection method; nonlinear systems; satellite attitude sensor faults; statistical technique; unscented Kalman filter; Analytical models; Convergence; Fault detection; Jacobian matrices; Linearization techniques; Nonlinear systems; Satellites; Sensor systems; Sufficient conditions; Testing;
  • fLanguage
    English
  • Journal_Title
    Aerospace and Electronic Systems, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9251
  • Type

    jour

  • DOI
    10.1109/TAES.2007.4285348
  • Filename
    4285348