Abstract: Direct blind equalization algorithm for Single-Input-Multiple-Output (SIMO) model is proposed. The algorithm is completely independent of channel order estimation. Through the relationship between signal subspace and truncated data covariance, zero-delay equalizer which has random phase rotation problem is investigated. The combined impulse response of the channels matrix and equalizer filter impulse coefficients is used to deal with phase rotation problem of the proposed equalizer, so that a novel blind equalization algorithm is presented in this paper. Unlike many known subspace methods, the algorithm proposed in this paper do not rely on signal and noise subspace separation of received data covariance, and is robust to channel order estimation. The batch processing program of the proposed equalization algorithm is introduced in this paper. Based on recursion and iteration methods, the adaptive processing program of the proposed algorithm is also presented in this paper. Consequently the algorithm can be used in time-varying environment and can be applied to on-line processing. Simulation results illustrate that the performance of the proposed algorithm is also well in the condition of overestimation or underestimation of channel order. Besides that, good Mean Square Error (MSE), Symbol Error Rate (SER) and convergence performance are also presented through the simulation.