A Broadband Beamformer Using Controllable Constraints and Minimum Variance

Abstract

The minimum variance distortionless response (MVDR) and the linearly constrained minimum variance (LCMV) beamformers are two optimal approaches in the sense of noise reduction. The LCMV beamformer can also reject interferers using linear constraints at the expense of reducing the degree of freedom in a limited number of microphones. However, it may magnify noise that causes a lower output signal-to-noise ratio (SNR) than the MVDR beamformer. Contrarily, the MVDR beamformer suffers from interference in output. In this paper, we propose a controllable LCMV (C-LCMV) beamformer based on the principles of both the MVDR and LCMV beamformers. The C-LCMV approach can control a compromise between noise reduction and interference rejection. Simulation results show that the C-LCMV beamformer outperforms the MVDR beamformer in interference rejection, and the LCMV beamformer in background noise reduction