Abstract: A method based on characteristic function and matrxi-*algebraic is proposed to solve the convolutive blind separation of Direct sequence spread spectrum signals through the multi-path channels.First,the signals model under the condition of multiple sensors is built and proved to be consistent with the basis of the Independent subspace analysis. Then the concept of independent subspace analysis is introduced ,also the Hessian of Characteristic functions of the DSSS signals are proved to be block diagonal.Finally the matrix decomposition theory of matrix-*algebraic is used to transform the joint block diagonalization of multiple matries into the problem of finding a generic matrix of the commutant algebra, which is correspond to the matrix-*algebraic formed by the Hessian of Characteristic functions of the observed signals. And the diagonalization of the generic matrix is proved to be equivalent with the Joint block diagnolization of some matrix-*algebraic. Then the original problem comes down to finding a random solution of a homogeneous linear equations. The theory analyze implies that the proposed algorithm is very robust if the sensor noise is gaussian and shares the same variance,whenever the noise is white or color. Computer simulation shows the validity and reliability of the algorithm in the condition of three DSSS signals. The result also demonstrates that the proposed algorithm has better performance and less constraints comparing with the exsiting algorithms.The only disadvantage is that there should be more sensors,but in the large sensor network,it can be easily satified.