Research on the algorithms of robust adaptive beamforming

In practical array signal processing systems, traditional adaptive beamforming algorithms will degrade if some exploited assumptions become wrong or imprecise. Therefore, the robustness of adaptive beamforming techniques against environmental and array imperfections is one of the key issues. Compared with traditional methods, robust beamforming brings about many improvements on array performances. In this paper, we present a brief review on recent developments of robust adaptive beamforming. After introducing the traditional MVDR based robust beamforming, we emphasize the new robust beamforming which uses the Support Vector Machines (SVMs) to improve the generalization performance over the traditional techniques. This paper presents the modified SVM-based cost function and illustrates how it can be used to linear beamforming. Simulation results show that the proposed SVM-based beamformer has the desired robust performance both in no-mismatch and mismatch situations.