Mixing Matrix Estimation in Underdetermined Blind Source Separation Based on Single Source Points Detection

Mixing matrix estimation is very important for underdetermined blind source separation. To solve the problems of existing methods for mixing matrix estimation such as low estimation accuracy, a detection method for single source points (SSPs) is proposed based on local stationarity and distribution symmetry in this paper, and then mixing matrix estimation is obtained through clustering algorithm. The proposed method does not require region division of hypersphere and is easy to operate, so as to effectively eliminate pseudo SSPs and improve the clustering features of observed signals. The simulation results show that the proposed method has higher accuracy than the traditional methods.