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
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