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

Arunabha Bagchi, Rajeeva Karandikar

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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
    Original languageUndefined
    Title of host publication31st IEEE Conference on Decision and Control
    Place of PublicationTucson, Arizona
    PublisherIEEE
    Pages1245-1246
    Number of pages0
    Publication statusPublished - 16 Dec 1992
    Event31st IEEE Conference on Decision and Control, CDC 1992 - Westin La Paloma, Tucson, United States
    Duration: 16 Dec 199218 Dec 1992
    Conference number: 31

    Publication series

    Name
    PublisherIEEE
    Volume1

    Conference

    Conference31st IEEE Conference on Decision and Control, CDC 1992
    Abbreviated titleCDC
    CountryUnited States
    CityTucson
    Period16/12/9218/12/92

    Keywords

    • IR-30898
    • METIS-141539

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