Most of blind channel identification algorithms cannot estimate the channel with common zeros and they are sensitive to the channel order error. Here, this paper proposes a new cross-relation-based semi-blind channel identification method. The algorithm uses the output data structure correlation matrix Wand builds a linear system of equations based on the orthogonal relationship between matrix W and channel vector. Some known symbols are utilized based on MLS criterion to build other equations. The closed form solution of channel response is derived by the least-square method. The proposed algorithm effectively overcomes many limitations of blind channel identification algorithms, avoids the selection of optimal weighted parameter that commonly appears in the traditional semi-blind methods with strong robustness to channel noise and channel order. Simulation results verify the effectiveness and superiority of the proposed algorithm.