Sequenced steering vector estimation for eigen-subspace projection robust adaptive beamformer

Abstract

Abstract Eigen-subspace projection (ESP) is one of the most popular methods of robust adaptive beamforming, and the key issue of ESP is the selection of the projection subspace. The traditional ESP method treats the signal subspace as the projection subspace, so it needs source enumeration for a prior. Another inherent defect of it is its poor performance at low SNR. In this paper, we study in detail two methods for ESP-based robust adaptive beamforming. The main idea underlying these methods is to use the sequenced steering vector estimation to invert the estimate of the subspace dimension for an arranged eigenvector matrix. Since the proposed methods work without source enumeration, it is simple to implement. In addition, simulation results are included to illustrate the effectiveness and robustness of the proposed method as compared to the conventional ESP methods and other widely used robust techniques.