Robust adaptive beamforming under uncertainty in source direction-of-arrival

Adaptive beamforming can be used as a method for estimating an unknown waveform from a source impinging on an array of sensors. When the direction-of-arrival (DOA) of the incoming signal is known, the minimum variance distortionless response (MVDR) beamformer provides a distortionless version of the signal while suppressing noise and interference. However, if there is a mismatch between the look direction of the beamformer and the actual DOA of the signal, there can be significant degradation in performance. We use a Bayesian approach with the MVDR criterion to derive an adaptive beamformer which has nearly optimal performance under good conditions, and is robust to uncertainty in DOA under poor conditions