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 improvementsFile | Dimensione | Formato | |
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