• DocumentCode
    3118552
  • Title

    General piecewise linear filtering problems with small observation noise

  • Author

    Pardoux, E. ; Roubaud, M.C.

  • Author_Institution
    INRIA, Valbonne, France
  • fYear
    1989
  • fDate
    13-15 Dec 1989
  • Firstpage
    232
  • Abstract
    An algorithm which is based on several Kalman filters running in parallel is presented. A test procedure for deciding which Kalman filter to follow, which produces a good estimate of the unobserved system process in a nonlinear filtering problem with piecewise linear dynamics and small observation noise is developed. The results generalize those of W.H. Fleming, D. Ji, and E. Pardoux (1988)
  • Keywords
    Kalman filters; filtering and prediction theory; Kalman filters; observation noise; piecewise linear dynamics; piecewise linear filtering; Extraterrestrial measurements; Filtering algorithms; Measurement standards; Nonlinear dynamical systems; Nonlinear filters; Piecewise linear approximation; Piecewise linear techniques; Signal to noise ratio; Stochastic systems; System testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Decision and Control, 1989., Proceedings of the 28th IEEE Conference on
  • Conference_Location
    Tampa, FL
  • Type

    conf

  • DOI
    10.1109/CDC.1989.70109
  • Filename
    70109