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Blind source separation using the spatial ambiguity functions

Blind source separation consists of recovering a set of signals of which only instantaneous linear mixtures are observed. This problem has been typically solved using statistical information available on source signals. Previously, we have introduced spatial time-frequency (t-f) distributions as a new and effective alternative to separate sources whose signatures are different in the t-f domain. This paper presents a new blind source separation method, exploiting difference in the ambiguity-domain signatures of the sources. The approach is based on the diagonalization of a combined set of spatial ambiguity functions. In contrast to existing techniques, the proposed approach allows the separation of Gaussian sources with identical spectral shape but with different ambiguity domain localization properties.