Adaptive and Robust Beamforming

Abstract This chapter is dedicated to the overview of the main results in the fields of adaptive beamforming and robust adaptive beamforming. The basic principles and main approaches to adaptive and robust adaptive beamforming are explained based on the narrowband point source signal model. In addition, the extensions of the basic principles and approaches to the general rank source model and wideband signal are given. The particular numerical algorithms for adaptive beamforming such as the gradient algorithm, the sample matrix inversion algorithm, and the projection adaptive beamforming algorithm are reviewed. The particular robust adaptive beamforming techniques are the diagonally loaded sample matrix inversion beamforming technique, the robust adaptive beamforming techniques with point and derivative mainbeam constraints, the generalized sidelobe canceler, the adaptive beamforming techniques robust against the correlation between the signal of interest and interferences such as spatial and forward-backward smoothing, the adaptive beamforming techniques robust against rapidly moving interferences, the eigenspace-based beamforming technique, the worst-case-based and doubly constrained robust adaptive beamforming techniques, the probabilistically constrained robust adaptive beamforming technique, the robust adaptive beamforming that uses as little as possible prior information, and others.