DocumentCode :
2413073
Title :
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
Link To Document :
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