Based on Bernoulli-Gaussian model and the sparseness of source signals, a new algorithm for estimating the mixing matrix is proposed in this paper. It estimates the mixing matrix by searching the cluster points which are found through the density of points in the region. In order to enhance the precision of the algorithm, the cost function is constructed to search the cluster points. The last simulations show the good performance of the proposed algorithm.