Table of Contents
International Scholarly Research Notices
Volume 2014, Article ID 260875, 8 pages
Research Article

Iterative Robust Capon Beamforming with Adaptively Updated Array Steering Vector Mismatch Levels

Department of Electronic Engineering and Information Science, University of Science and Technology of China, Hefei 230027, China

Received 12 April 2014; Revised 17 July 2014; Accepted 22 July 2014; Published 3 November 2014

Academic Editor: Wei Liu

Copyright © 2014 Tao Zhang and Liguo Sun. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


The performance of the conventional adaptive beamformer is sensitive to the array steering vector (ASV) mismatch. And the output signal-to interference and noise ratio (SINR) suffers deterioration, especially in the presence of large direction of arrival (DOA) error. To improve the robustness of traditional approach, we propose a new approach to iteratively search the ASV of the desired signal based on the robust capon beamformer (RCB) with adaptively updated uncertainty levels, which are derived in the form of quadratically constrained quadratic programming (QCQP) problem based on the subspace projection theory. The estimated levels in this iterative beamformer present the trend of decreasing. Additionally, other array imperfections also degrade the performance of beamformer in practice. To cover several kinds of mismatches together, the adaptive flat ellipsoid models are introduced in our method as tight as possible. In the simulations, our beamformer is compared with other methods and its excellent performance is demonstrated via the numerical examples.