Near-field frequency domain blind source separation for convolutive mixtures

The paper presents a method for solving the permutation problem of frequency domain blind source separation (BSS) when source signals come from the same or similar directions. Geometric information such as the direction of arrival (DOA) is helpful for solving the permutation problem, and a combination of the DOA based and correlation based methods provides a robust and precise solution. However, when signals come from similar directions, the DOA based approach fails, and we have to use only the correlation based method whose performance is unstable. We show that an interpretation of the ICA solution by a near-field model yields information about spheres on which source signals exist, which can be used as an alternative to the DOA. Experimental results show that the proposed method can robustly separate a mixture of signals arriving from the same direction.