Underdetermined Blind Radar Signal Separation Based on ICA
Chen Xiao-jun Cheng Hao Tang Bin (College of Electronic Engineering,University of Electronic Science Technology of China,Chengdu 610054,China)
A method of the mixing matrix estimation in the underdetermined source separation is proposed in which the sources are not sparse enough to estimate the mixing matrix. Getting many sub matrixes through applying Independent component analysis(ICA) for observation signals and removing the elements do not belong to the mixing matrix,the mixing matrix is estimated precisely with C-means clustering agglomeration. Then,the source signals can be recovered with the statistically sparse decomposition principle. The experiment shows that the method have better accuracy and validity than K-means and searching-and-averaging method in the time domain in estimating the mixing matrix.
【CateGory Index】： TN957.51