Mixing Matrix Estimation Method for UBSS based on Observed Data Segmentation

Abstract

This paper presents a mixing matrix estimation method for underdetermined blind source separation (UBSS) when source signals are insufficiently sparse. Main ideas are as follows: Observed signals are segmented. Then mixing matrices for every segment of observed signals are estimated using overdetermined blind source separation (OBSS) algorithms, and these mixing matrices are obtained, forming a mixing matrix combination. The fuzzy c-means (FCM) method is adopted to process the mixing matrix combination, obtaining the final number of source signals and mixing matrix. This estimation method assumes that source signals are independent but unnecessarily sparse. To verify the effectiveness of this estimation method, simulations are performed at the aspects of close arrival angles of source signals, changes in the segmentation length of observed signals, and changes in the number of source and observed signals.