Robust adaptive beamforming with partly calibrated arrays in the presence of gain-phase errors

The performance of the beamformer, especially the beamformer based on the interference plus noise covariance matrix (INCM) reconstruction which needs accurate array manifold knowledge, will degrade dramatically in the presence of gain-phase errors. To solve this problem, we propose a robust adaptive beamforming method based on partly calibrated arrays (PCA). The main idea of this method is to estimate the gain-phase errors more accurately using the higher signal-to-noise ratio (SNR) signal sources and the PCA. After that, we calibrate the interference signal steering vector (SV) and reconstruct the more accurate INCM based on the estimation results. Finally, the SV of the desired signal is estimated by the intersection of two special subspaces. On the basis of the above research, the optimal weight vector is obtained. Numerical simulation results demonstrate the superior performance of the proposed beamformer relative to other existing beamformers in the presence of gain-phase errors.