A robust beamforming algorithm based on covariance matrix reconstruction is proposed to solve the sensitivity problem of Capon beamforming under error condition. The algorithm divides the spatial domain of the signal set into interference region and signal region, and then divides the two regions into several independent and non-overlapping parts. The interference covariance matrix is constructed by integrating the interference region, and then the noise covariance matrix is reconstructed by using the minimum eigenvalue of the sample covariance matrix. Finally, the expected signal guidance vector error is modeled by the ring uncertainty set, and the Capon spectrum integration is performed on the ring uncertainty set to estimate the expected signal covariance matrix, and the expected signal guidance vector is obtained according to its main eigenvector. Simulation results show that compared with the traditional robust beamforming algorithm, the performance of this method is more excellent and stable under the conditions of different snapshot numbers and input Signal-to-Noise Ratio(SNR). At the same time, it bears the advantage of low computation.