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EnglishThis work presents a polynomial version of the well-known extended Kalman filter (EKF) for the state estimation of nonlinear discrete-time stochastic systems. The proposed filter, denoted polynomial EKF (PEKF), consists in the application of the optimal polynomial filter of a chosen degree m to the Carleman approximation of a nonlinear system. When m=1 the PEKF algorithm coincides with the standard EKF. For the filter implementation the moments of the state and output noises up to order 2 are required. Numerical simulations compare the performances of the PEKF with those of some other existing filters, showing significant improvements.
| Titolo: | Polynomial Extended Kalman Filter | |
| Autori: | ||
| Data di pubblicazione: | 2005 | |
| Rivista: | ||
| Abstract: | This work presents a polynomial version of the well-known extended Kalman filter (EKF) for the state estimation of nonlinear discrete-time stochastic systems. The proposed filter, denoted polynomial EKF (PEKF), consists in the application of the optimal polynomial filter of a chosen degree m to the Carleman approximation of a nonlinear system. When m=1 the PEKF algorithm coincides with the standard EKF. For the filter implementation the moments of the state and output noises up to order 2 are required. Numerical simulations compare the performances of the PEKF with those of some other existing filters, showing significant improvements. | |
| Handle: | http://hdl.handle.net/11697/18094 | |
| Appare nelle tipologie: | 1.1 Articolo in rivista |
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