• DocumentCode
    358172
  • Title

    Linear filtering system with arbitrary initial conditions

  • Author

    Xi Wu ; Yau, Stephen S T

  • Author_Institution
    Dept. of Math. Stat. & Comput. Sci., Illinois Univ., Chicago, IL, USA
  • Volume
    2
  • fYear
    2000
  • fDate
    2000
  • Firstpage
    785
  • Abstract
    We consider linear filtering system with non-Gaussian initial condition. Two explicit and simple filtering formulae are obtained: one for the conditional density function of the estimated state and another for the conditional mean. Only 2n sufficient statistics need to be computed in real time, where n is the dimension of the state vector. It is shown that our formulae constitute natural extensions of the Kalman-Bucy filter. We also give an explicit solution to the derived Kolmogorov equation
  • Keywords
    filtering theory; matrix algebra; partial differential equations; probability; state estimation; 2n sufficient statistics; Kalman-Bucy filter; Kolmogorov equation; conditional density function; conditional mean; explicit solution; linear filtering system; nonGaussian initial condition; Density functional theory; Equations; Filtering theory; Mathematics; Maximum likelihood detection; Nonlinear filters; Signal processing; State estimation; Statistics; Vectors;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    American Control Conference, 2000. Proceedings of the 2000
  • Conference_Location
    Chicago, IL
  • ISSN
    0743-1619
  • Print_ISBN
    0-7803-5519-9
  • Type

    conf

  • DOI
    10.1109/ACC.2000.876605
  • Filename
    876605