Filtering for linear systems driven by fractional Brownian motion

Author

Ahmed, N.U. ; Charalambous, C.D.

Author_Institution

Sch. of Inf. Technol. & Eng., Ottawa Univ., Ont., Canada

Volume

5

fYear

2000

fDate

2000

Firstpage

4259

Abstract

In this paper we study continuous time filtering for linear systems driven by fractional Brownian motion processes. We present the derivation of the optimum linear filter equations which involve a pair of functional-differential equations giving the error covariance (matrix-valued) function and the filter. These equations are the appropriate substitutes of the matrix-Riccati differential equation arising in classical Kalman filtering. However the optimum filter has the classical appearance and, as usual, it is driven by the increments of the observed process

Keywords

Brownian motion; covariance matrices; differential equations; filtering theory; functional equations; optimisation; paper; classical Kalman filtering; continuous time filtering; error covariance function; fractional Brownian motion; functional-differential equations; linear systems; matrix-Riccati differential equation; matrix-valued function; optimum filter; optimum linear filter equations; Brownian motion; Covariance matrix; Differential equations; Filtering; Information technology; Linear systems; Matrices; Nonlinear filters; Random processes; Stochastic processes;

fLanguage

English

Publisher

ieee

Conference_Titel

Decision and Control, 2000. Proceedings of the 39th IEEE Conference on

Conference_Location

Sydney, NSW

ISSN

0191-2216

Print_ISBN

0-7803-6638-7

Type

conf

DOI

10.1109/CDC.2001.914568

Filename

914568