The existing MIMO-OFDM channel estimation method based on compressed sensing uses multiple orthogonal matching pursuit algorithm and its improved algorithm. For such a large-scale data reconstruction algorithm has high computational complexity, storage capacity and other issues, MIMO-OFDM sparse channel estimation method based on the gradient pursuit algorithm is proposed. Gradient pursuit algorithm uses the steepest descent method for the objective function optimal solution, namely calculating the search direction of the objective function and the search step with each iteration, and selecting the optimal solution every atom iterative reconstruction values. As used herein, the estimation performance of gradient pursuit algorithm is compared with the performance of traditional least squares estimation algorithm and orthogonal matching pursuit algorithm. The simulation results show that the gradient pursuit algorithm can guarantee a better estimate and reduce the pilot overhead and the computational complexity. Therefour, the efficiency of reconstruction is improved.