Semi-blind source separation for convolutive mixtures based on frequency invariant transformation

A novel method for separation of a class of convolutive mixtures is proposed, in which the received sensor signals are first transformed into instantaneous mixtures and then standard blind source separation (BSS) algorithms for instantaneous mixtures are applied. Since partial information about the mixing mechanism is required in the design of the transformation, the proposed method is strictly speaking semi-blind. From the beamforming viewpoint, the proposed approach represents a blind broadband beamforming method. As the separation is performed in fullband and only one separation is needed, the permutation problem associated with the frequency-domain BSS is avoided and the separation can be easily implemented online. Simulation results verify the usefulness of the proposed method.