A Time-Frequency Technique for Blind Separation and Localization of Pure Delayed Sources

In this paper we address the problem of overdetermined blind separation and localization of several sources, given that an unknown scaled and delayed version of each source contributes to each sensor recording. The separation is performed in the time-frequency domain via an Alternating Least Squares (ALS) algorithm coupled with a Vandermonde structure enforcing strategy across the frequency mode. The latter allows to update the delays and scaling factors of each source with respect to all sensors, up to the ambiguities inherent to the mixing model. After convergence, a reference sensor can be chosen to remove these ambiguities and the Time Difference of Arrival (TDOA) estimates can be exploited to localize the sources individually.