When the desired signal is present in training snapshots, the adaptive beamforming is very sensitive to the mismatch represented by the steering vector mismatch, and its performance degrades rapidly.This situation will be more serious when there is jammer in motion at the same time.To solve the problem, a robust adaptive beamforming algorithm based on covariance matrix taper and steering vector estimation is proposed.The algorithm weights the sample covariance matrix to enhance it, and then estimates the real steering vector by using the enhanced covariance matrix.Finally, the enhanced covariance matrix and the estimated steering vector are used for beamforming.The simulation results show that the proposed algorithm can overcome model mismatch while broadening the null notch, which improves the robustness of the beamformer to jammer in motion and model mismatch.