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 language | Undefined |
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Title of host publication | 31st IEEE Conference on Decision and Control |
Place of Publication | Tucson, Arizona |
Publisher | IEEE |
Pages | 1245-1246 |
Number of pages | 0 |
Publication status | Published - 16 Dec 1992 |
Event | 31st IEEE Conference on Decision and Control, CDC 1992 - Westin La Paloma, Tucson, United States Duration: 16 Dec 1992 → 18 Dec 1992 Conference number: 31 |
Publication series
Name | |
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Publisher | IEEE |
Volume | 1 |
Conference
Conference | 31st IEEE Conference on Decision and Control, CDC 1992 |
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Abbreviated title | CDC |
Country/Territory | United States |
City | Tucson |
Period | 16/12/92 → 18/12/92 |
Keywords
- IR-30898
- METIS-141539