The invention relates to an alias matrix estimating method of the blind separation of sparse sources with unknown numbers, which belongs to the engineering field and more particularly relates to the technical field of the blind source separation. The method aims at solving the problems that the existing alias matrix estimating method of the blind separation of the sparse sources on the basis of a classic clustering algorithm requires that the number of source signals is known and the estimating precision is poorer. According to the geometric feature that sparse source alias signals present linear clustering and on the basis of the distance relation of a clustering center and each sort of data dense point, the invention provides a novel clustering validity criterion and estimates the number of the source signals according to the criterion. At the same time, each sort of data dense point is found out by making use of Hough transformation so as to substitute the clustering center to estimate the alias matrix, thereby improving the estimating precision of the alias matrix. The method of the invention is suitable for the estimation for the alias matrix of the blind separation of the sparse sources under the condition that the number of the source signals is unknown and is widely applied to the fields of speech recognition, medical signal processing, wireless communication, and so on, and the estimating precision of the alias matrix is improved.