In a hearing aid application, the performance of an adaptive beamformer is sensitive to errors in the acoustic transfer function or noise estimation. The estimation errors can be caused by factors including the head movement of the hearing aid users, non-stationarity of the environment, or imperfect array calibration. With such inaccurate information, the beamformer not only provides less noise reduction, but also causes undesirable speech distortions. To improve the beamformers performance in such conditions, robust beam-forming algorithms have been proposed in the literature. In particular, to minimize the speech distortions caused by imperfect look direction estimation, a robust binaural beam-forming algorithm has been proposed in . This algorithm utilizes constrained optimization to improve the protection of the target speech. The beamforming adaption is based on a low-complexity iteration method called Alternating Direction Method of Multipliers (ADMM). This paper aims for evaluating the proposed binaural beamforming algorithm by comparing its performance with the Minimum Variance Distortionless Response (MVDR) beamformer in various noisy environments. The benefit of the proposed algorithm is demonstrated through both objective and subjective evaluations. In particular, multiple-microphone recordings on a pair of binaural hearing aids on a mannequin are used. Objective perception scores are calculated and compared. In addition, a subjective evaluation of speech intelligibility using normal-hearing listeners is conducted. Both the objective and subjective evaluation results show the robustness of the proposed algorithm.