Time difference of arrival estimation of sound source using Cross Correlation and modified maximum likelihood weighting function

Abstract

The Generalized Cross Correlation (GCC) framework is one of the most widely used methods for Time Difference of Arrival (TDOA) estimation and Sound Source Localization (SSL). TDOA estimation using cross correlation without any pre-filtering of the received signals has a large amount of errors in real environments. Thus, several filters (weighting functions) have been proposed in the literature to improve the performance of TDOA estimation. These functions aim to mitigate TDOA estimation error in noisy and reverberant environments. Most of these methods consider the noise or reverberation and as one of them increases, TDOA estimation error increases. In this paper, we proposed a new weighting function. This function is a combined and modified version of Maximum Likelihood (ML) and PHAT-rg functions. We named our proposed function as Modified Maximum Likelihood with Coherence (MMLC). This function has merits of both the ML and PHAT-rg functions and can work properly in both noisy and reverberant environments. We evaluate our proposed weighting function using real and synthesized datasets. Simulation results shows that our proposed filter has better performance in terms of TDOA estimation error and anomalous estimations