• DocumentCode
    486909
  • Title

    Linearized Reduced Order Filtering

  • Author

    Nagpal, Krishan ; Sims, Craig

  • Author_Institution
    DEPARTMENT OF ELECTRICAL ENGINEERING, WEST VIRGINIA UNIVERSITY, MORGANTOWN, WEST VIRGINIA 26506
  • fYear
    1987
  • fDate
    10-12 June 1987
  • Firstpage
    426
  • Lastpage
    429
  • Abstract
    When a nonlinear dynamical or observational model is used to describe a system, the Kalman filter cannot be used to estimate the state without some approximation being made. If the approximation used is linearization of the equations about the state estimate, the resulting modification of the Kalman filter is often called an extended Kalman filter. In this paper we obtain a similar result, where the filter is constrained to be of reduced order to avoid excessive computational complexity.
  • Keywords
    Atmosphere; Atmospheric modeling; Computational complexity; Filtering; Kalman filters; Linear approximation; Nonlinear equations; Nonlinear filters; Riccati equations; State estimation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    American Control Conference, 1987
  • Conference_Location
    Minneapolis, MN, USA
  • Type

    conf

  • Filename
    4789358