Robust adaptive beamforming: Evolution of approaches, analysis, and comparison.

Abstract

A so-called worst-case-based robust adaptive beamforming approach has been proposed a few years ago. This approach has been followed up by a number of works, which significantly improved the implementation issues. Recently, two new approaches have been developed: the probability constrained based and sequential quadratic programing based approaches. The probability constraint based design requires the distortionless response constraint to be kept with a certain selected probability, while the worst-case-based design requires this constraint to be kept for the worst-case operational conditions. The sequential quadratic programing based approach uses the iterative estimation of the signal steering vector and, therefore, is significantly different from two two aforementioned designs. In this paper, we overview, analyze, and compare all the aforementioned approaches to robust adaptive beamforming design.