To solve the problem of excessive computational complexity of traditional beamforming, a constrained adaptive beamforming algorithm based on set-membership and conjugate gradient is proposed. By using the principle of the conjugate gradient algorithm, the output variance is minimized under the constraint of keeping the desired signal power, then the weight vector is obtained, the calculation of the input signal covariance inverse matrix is avoided, and convergence is effectively achieved. Setmembership applies dataselective updates by using time varying boundary constraints to reduce the computational complexity. The algorithm avoids repetitive computation and obtains effective weight vector by using the set-membership and conjugate gradient. Computational complexity and convergence performance analysis of the algorithm are provided. Simulation results show the enhanced convergence performance and low computational complexity of the proposed algorithm compared with traditional algorithms.