Calibration of microphone arrays with an uncalibrated source

摘要

Microphone array calibration that does not require a calibrated source or calibrated reference microphone is provided. We provide a statistical (Bayesian) algorithm that (under condition of reasonable environment noise during calibration) can determine gain and phase differences of a whole array at once, even when the gain and/or phase of the source is unknown. More specifically, a Bayesian regression with complex log-normal prior and complex normal likelihood is employed. The inherent phase-wrapping ambiguity in this regression is resolved by exploiting the similarity of likelihood between a lattice point and its Euclidean Voronoi region.