Robust adaptive beamforming using data dependent constraints

Abstract
An adaptive beamformer which is robust to uncertainty in source DOA is derived. The beamformer is a weighted sum of minimum variance distortionless response (MVDR) beamformers pointed at a set of candidate DOAs, where the relative contribution of each MVDR beamformer is determined from a combination of observed data and prior knowledge about the DOA. When SNR is high, the MVDR beamformer whose look direction is closest to the source dominates, and nearly optimal performance is obtained. When SNR is low, the weighted combination of beamformers has a wider main beam which is robust to DOA uncertainty.

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