An Adaptive Non-Linear Process for Under-Determined Virtual Microphone Beamforming

Virtual microphone beamforming techniques are attractive for devices limited by space constraints. These techniques synthesize virtual microphone signals via interpolation algorithms. We propose to extend existing virtual microphone signal interpolation by employing an adaptive non-linear (ANL) process for acoustic beamforming. The proposed ANL based interpolation utilizes a target-presence probability criteria to determine the degree of non-linearity. The beamformer output is then derived using a combination between interpolations during target inactive zones and target active zones. Such combination offers a trade-off between reducing interference and target signal distortion. We apply the proposed ANL-based interpolator to the maximum signal-to-noise ratio (MSNR) beamformer and compare its performance against conventional beamforming and virtual microphone based beamforming methods in under-determined situations.