Robust Wavelet Kalman Filter

Since Kalman filter and wavelet transform techniques are both suitable for a nonstationary process, wavelet-Kalman filter was proposed and applied to various industrial fields. However, the wavelet-Kalman filter subjected to model uncertainty with nonstationary process has not been considered. Thus, the robust wavelet-Kalman filter method is proposed in this paper. The proposed method can prevent the degradation of filter performance when parameter uncertainty exists in both the state and measurement matrices and preserve the merits of the standard Kalman filter in the sense that it produces optimal estimates. A simple example shows that the proposed approach outperforms the standard Kalman filter and the nominal wavelet-Kalman filter.