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 mu to the Carleman approximation of a nonlinear system. When mu = 1 the PEKF algorithm coincides with the standard EKE, For the filter implementation the moments of the state and output noises up to order 2mu are required. Numerical simulations compare the performances of the PEKF with those of some other existing filters, showing significant improvements

Germani, A., Manes, C., Palumbo, P. (2005). Polynomial extended Kalman filter. IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 50(12), 2059-2064 [10.1109/TAC.2005.860256].

Polynomial extended Kalman filter

Palumbo, P
2005

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 mu to the Carleman approximation of a nonlinear system. When mu = 1 the PEKF algorithm coincides with the standard EKE, For the filter implementation the moments of the state and output noises up to order 2mu are required. Numerical simulations compare the performances of the PEKF with those of some other existing filters, showing significant improvements
Articolo in rivista - Articolo scientifico
Extended Kalman Filtering; nonlinear stochastic systems; polynomial filtering
English
2005
50
12
2059
2064
reserved
Germani, A., Manes, C., Palumbo, P. (2005). Polynomial extended Kalman filter. IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 50(12), 2059-2064 [10.1109/TAC.2005.860256].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/246697
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