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

Bagchi, Arunabha and Karandikar, Rajeeva (1992) White noise theory of robust nonlinear filtering with correlated state and observation noises. In: 31st IEEE Conference on Decision and Control, December 1992, Tucson, Arizona.

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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
Item Type:	Conference or Workshop Item
Copyright:	© 1992 IEEE
Faculty:	Electrical Engineering, Mathematics and Computer Science (EEMCS)
Research Group:	Stochastic Systems and Signals (SST)
Link to this item:	http://purl.utwente.nl/publications/30898
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