Optimal beamforming as a time domain equalization problem with application to room acoustics

Signals captured by microphone arrays provide spatial diversity that can be exploited by multichannel processing algorithms to suppress noise and reverberation. Beamforming is a class of approaches that treats the problem with respect to the spatial location of wanted and competing sources, leveraging properties of propagation of waves in free space. A related class of algorithms is channel equalization that exploits knowledge of the acoustic impulse response between a source and microphones with a view to near-perfect dereverberation. Beamforming has been shown to be a very powerful and practical tool in a number of domains, whereas channel equalizers are notoriously sensitive to noise and channel mismatch leading to limited practical applicability. This paper investigates some of the common properties of these algorithms and presents a solution incorporating approaches from both disciplines.