A Novel Multiple Sparse Source Localization Using Triangular Pyramid Microphone Array

Making use of the time-frequency spectra sparsity of the speech sources and the spatial and inter-relation information provided from a triangular pyramid microphone array (TPMA), the ratio of the inter-sensor phase difference (RIPD) is defined and a direct relationship between RIPD information and the direction of arrival (DOA) of each source is obtained. A novel multiple speech source localization algorithm (named as TPMA-RIPD) using the histogram clustering technique is proposed, which has been evaluated by several simulation experiments. Experimental results show that the TPMA-RIPD algorithm is able to provide high source localization accuracy in noisy environment for all angles. It is also able to estimate multiple speech sources when the number of sources is larger than that of the microphones used.