Simultaneous Interference Localization and Array Calibration for Robust Adaptive Beamforming With Partly Calibrated Arrays

In this article, we address the problem of robust adaptive beamforming in the presence of array sensor miscalibration. We consider the use of partly calibrated linear arrays, where only a small portion of sensors have been gain-phase aligned. Our solution is based on the interference-plus-noise covariance matrix (INCM) reconstruction principle. In our solution, the INCM is reconstructed by performing simultaneous interference localization and array calibration (SILAC). Toward this end, a novel virtual baseline extension technique is presented for high-accuracy SILAC. After SILAC, the interference and noise powers are estimated, and the INCM is reconstructed subsequently. No computations of integration/summation and nonlinear optimization are involved in our beamformer, which is termed as “INCM-SILAC” beamformer. Numerical examples are offered to validate the performance of the INCM-SILAC beamformer. A MATLAB code for reproducing the results of radar application example is available at https://github.com/jinhesjtu/SILAC.git