Online Blind Extraction Algorithm For WSN Signal Based on UKF

Recently, a class of online blind extraction algorithms in the framework of Kalman filtering have been developed for wireless sensor networks applications. But their performance is poor when additive noise is not neglectable. To address this issue, a new blind extraction method is proposed. This method novelly adopts two unscented Kalman filters alternately estimate the extraction vector and the source signal. Thereby, an optimal estimation of the source signal in sense of minimum mean square error is obtained. Simulation result indicates that the proposed algorithm can effectively extract target signal, and outperforms the existing unscented Kalman approach.