• DocumentCode
    869859
  • Title

    An optimal reduced-order stochastic observer-estimator

  • Author

    Hong, Lang

  • Author_Institution
    Dept. of Electr. Eng., Wright State Univ., Dayton, OH, USA
  • Volume
    28
  • Issue
    2
  • fYear
    1992
  • fDate
    4/1/1992 12:00:00 AM
  • Firstpage
    453
  • Lastpage
    461
  • Abstract
    An optimal reduced-order observer-estimator (filter) is developed which can provide a full-dimensional vector of state estimates for systems where the dimension of the measurement vector is smaller than that of the state vector and none of the measurements are noise free. The reduced-order filter consists of two subfilters each of which provides a subset of the optimal estimate. A two-step L-K transformation is employed to minimize the estimate error variance of each subfilter. The optimal reduced-order filter developed is computationally efficient
  • Keywords
    estimation theory; filtering and prediction theory; minimisation; state estimation; stochastic processes; error variance; full-dimensional vector; optimal reduced-order stochastic observer-estimator; reduced-order filter; state estimates; state vector; subfilter; two-step L-K transformation; Large-scale systems; Noise measurement; Noise reduction; Nonlinear filters; Satellites; Space stations; State estimation; Stochastic processes; Stochastic resonance; Stochastic systems;
  • fLanguage
    English
  • Journal_Title
    Aerospace and Electronic Systems, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9251
  • Type

    jour

  • DOI
    10.1109/7.144571
  • Filename
    144571
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=869859