Euclidean Distance Matrices Application in Sound Source Localization

Abstract

In Sound source localization literature there are two main different approaches to find the location of a sound source, TDOA-based and ILD-based methods. TDOA-based methods use time differences of arrival, and ILD-based methods use intensity level differences, both to obtain the direction or location of the sound source. ILD-based methods need accurate measurements and they are vulnerable to noise. In 2D sound source localization, by using only an ILD-based or TDOA-based method, there are needed at least three microphones to find the location of a sound source. However, recently some papers have used both methods simultaneously to decrease the microphones count. Sound source localization consists of two steps, TDs or ILDs measurement step, and after that, the location calculation step. This paper investigates a 2D sound source localization technique using only two microphones by exploiting Euclidean distance matrices theory in the second step. The simulation results confirm that this technique is applicable to calculate the location of a sound source using ILD and TDOA measured values simultaneously.