White noise theory of robust nonlinear filtering with correlated state and observation noises

Author

Bagchi, Arunabha ; Karandikar, Rajeeva

Author_Institution

Dept. of Appl. Math., Twente Univ., Enschede, Netherlands

fYear

1992

fDate

1992

Firstpage

1245

Abstract

In the direct white noise theory of nonlinear filtering, the state process is still modeled as a Markov process satisfying an Ito stochastic differential equation, while a finitely additive white noise is used to model the observation noise. In the present work, this asymmetry is removed by modeling the state process as the solution of a (stochastic) differential equation with a finitely additive white noise as the input. This makes it possible to introduce correlation between the state and observation noise, and to obtain robust nonlinear filtering equations in the correlated noise case

Keywords

filtering and prediction theory; observability; stochastic systems; white noise; Markov process; correlated state; direct white noise theory; filtering equations; finitely additive white noise; observation noises; robust nonlinear filtering; state noise; stochastic differential equation; Additive white noise; Differential equations; Filtering theory; Gaussian processes; Indium tin oxide; Markov processes; Mathematics; Noise robustness; Nonlinear equations; Stochastic resonance; Topology; White noise;

fLanguage

English

Publisher

ieee

Conference_Titel

Decision and Control, 1992., Proceedings of the 31st IEEE Conference on

Conference_Location

Tucson, AZ

Print_ISBN

0-7803-0872-7

Type

conf

DOI

10.1109/CDC.1992.371516

Filename

371516