A tunable beamformer for robust superdirective beamforming

Abstract

Conventional superdirective beamforming is a well-known multi-microphone enhancement method with superior directivity factor (DF). However, it suffers from an inferior white noise gain (WNG), which is expressed by high sensitivity to uncorrelated noise and array inaccuracies. In this work, a beamformer with tunable superdirective gain is introduced. The proposed approach plays a role of a regularized superdirective beamformer, where instead of constraining the WNG, we minimize both white noise and diffuse noise energy in the optimization problem. In addition, by using a tunable regularization parameter, we control the amount of the beamformer DF and WNG. This single boresight solution is then extended to a multiple linear constraint beamformer, with any user-determined spatial or frequency constraints. The beamformer gain response simulations exhibit a robust and controllable solution with an efficient DF/WNG tradeoff.