Robust adaptive beamforming against the array pointing error

Minimum variance distortionless response (MVDR) beamformer is a technique for receiving the desired signal from specific direction while suppressing the interfering signals adaptively from other directions using an array of sensors. This technique is able to automatically optimize the array pattern by adjusting the elemental control weights until a prescribed objective function is satisfied. That is, it provides a means for separating a desired signal from interfering signals. It has been widely used in array signal processing, such as radar, sonar, seismology, wireless communications, microphone array speech processing and other areas. Unfortunately, the MVDR beamformer is more sensitive to array errors, such as the array pointing error caused by direction of arrival mismatch, imprecise array calibration or any other possible factors, especially in the case of high signal-to-noise ratio (SNR). In this paper, a robust adaptive beamforming against the array error is proposed. With the knowledge of the presumed direction of arrival (DOA) of the desired signal, the interference-plus-noise covariance matrix can be reconstructed based on the spatial spectrum distribution, which improves the stability of algorithm. Based on the power method, the presumed steering vector of the signal is corrected to improve the performance of deteriorated beamformer efficiently when array errors exist. Additionally, the proposed approach makes use of the Frame method to obtain the inverse of the interference-plus-noise covariance matrix, so that it avoids the complexities of matrix inversion. Compared with the previous algorithms, the proposed algorithm has good performance and can be implemented easily without any specific optimization software. Simulation results are presented to verify the effectiveness of the proposed method.