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
Link To Document :
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