Microphone Pair Selection for Sound Source Localization in Massive Arrays of Spatially Distributed Microphones

In massive distributed microphone arrays, such as in conference systems, the use of all sensors leads to unnecessary energy consumption and limited network life, as some sensors may have a limited contribution to specific estimation tasks, such as sound source localization (SSL). In this work, we propose two pre-processing methods for microphone pair selection in steered response power (SRP) based SSL using massive arrays of spatially distributed microphones. The first method is based on thresholding which results in a selection of broadside microphone pairs, that is, microphone pairs that are oriented broadside to the source direction, and only the signals from those microphones are collected for use in the SRP algorithm. The second method is based on sparseness of the cross-correlation in which the pairs which have a high sparsity factor are selected for use in localization. These methods are further improved by leveraging orientational diversity. Simulations show that we achieve a localization performance only using the selected microphone pairs that is comparable to the performance when all microphones are employed.