Robust Widely Linear Beamforming via an IAA Method for the Augmented IPNCM Reconstruction
Jiangbo Liu, Guan Gui, Wei Xie, Xunchao Cong, Qun Wan, Fumiyuki Adachi · IEICE Transactions on Fundamentals of Electronics Communications and Computer Sciences · 2017
Based on the reconstruction of the augmented interference-plus-noise (IPN) covariance matrix (CM) and the estimation of the desired signal's extended steering vector (SV), we propose a novel robust widely linear (WL) beamforming algorithm. Firstly, an extension of the iterative adaptive approach (IAA) algorithm is employed to acquire the spatial spectrum. Secondly, the IAA spatial spectrum is adopted to reconstruct the augmented signal-plus-noise (SPN) CM and the augmented IPNCM. Thirdly, the extended SV of the desired signal is estimated by using the iterative robust Capon beamformer with adaptive uncertainty level (AU-IRCB). Compared with several representative robust WL beamforming algorithms, simulation results are provided to confirm that the proposed method can achieve a better performance and has a much lower complexity.