Adaptive Beamforming Based on Interference Covariance Matrix Estimation

Abstract

In this paper, we propose a robust adaptive beam-forming algorithm, where the interference-plus-noise covariance matrix is estimated by identifying and removing the desired signal component from the sample covariance matrix. For this purpose, we construct a desired signal subspace and its orthogonal subspace to identify the eigenvector of the sample covariance matrix corresponding to the desired signal. The adaptive beam-former is then designed using the estimated interference-plus-noise covariance matrix and the identified signal eigenvector. Because both are independent of the knowledge of the array geometry, the proposed adaptive beamformer is robust to array model mismatch. Simulation results demonstrate the effectiveness of the proposed robust adaptive beamforming algorithm.