• DocumentCode
    813217
  • Title

    Identification of optimum filter steady-state gain for systems with unknown noise covariances

  • Author

    Carew, Burian ; Belanger, Pierre R.

  • Author_Institution
    McGill University, Montreal, Canada
  • Volume
    18
  • Issue
    6
  • fYear
    1973
  • fDate
    12/1/1973 12:00:00 AM
  • Firstpage
    582
  • Lastpage
    587
  • Abstract
    A discrete linear stationary system is considered for which the input noise covariance Q and the output noise covariance R are unknown. A stable filter with a suboptimal gain is assumed. An identification scheme is presented which uses the autocorrelation functions of the innovations sequence of the suboptimal filter to determine the optimum filter steady state gain \\Gamma directly without the intermediate determination of the unknown covariances Q and R . The approach used is to identify an output equivalent representation of the original system which does not involve the unknown covariances directly.
  • Keywords
    Innovations methods; Linear systems, stochastic discrete-time; State estimation; Autocorrelation; Equations; Hafnium; Kalman filters; Nonlinear filters; Observability; Steady-state; Technological innovation; Variable speed drives;
  • fLanguage
    English
  • Journal_Title
    Automatic Control, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9286
  • Type

    jour

  • DOI
    10.1109/TAC.1973.1100420
  • Filename
    1100420