In our recent work an effective method for multiple source localization has been proposed under the name of cumulative State Coherence Transform (cSCT). Exploiting the physical meaning of the frequency-domain blind source separation and the sparse time-frequency dominance of the acoustic sources, multiple reliable TDOAs can be estimated with only two microphones, regardless of the permutation problem and of the microphone spacing. In this paper we present a multidimensional generalization of the cSCT which allows one to localize several sources in the P-dimensional space. An important approximation is made in order to perform a disjoint TDOA estimation over each dimension which reduces the localization problem to linear complexity. Furthermore the approach is invariant to the array geometry and to the assumed acoustic propagation model. Experimental results on simulated data show a precise 2-D localization of 7 sources by only using an array of three elements.
['Francesco Nesta', 'Maurizio Omologo']
Generalized State Coherence Transform for multidimensional localization of multiple sources