Blind channel identification can be cast into a single-input-multi-output (SIMO) identification problem by oversampling and then solved easily by SIMO identification methods. Due to this, SIMO identification is of great interest and attracts a lot of attention in the past twenty years. Many efficient methods have been developed for this problem. However, most of them are sensitive to overestimation of channel order. Based on sparse representation, an efficient SIMO identification method is proposed in this paper. Differing from the Prediction Error Method, the new algorithm does not require the input signal to be independent and identical distribution, and even the input signal can be non-stationary. In addition, the new algorithm is more robust to the overestimation of channel order.