Robust Stochastic Maximum Likelihood Algorithm for DOA Estimation of Acoustic Sources in the Spherical Harmonic Domain

Abstract

The direction of arrival (DOA) estimation of the sound sources has been a popular signal processing research topic due to its widespread applications. Using spherical microphone array, DOA estimation can be applied in the spherical harmonic (SH) domain without any spatial ambiguity. However, the environment reverberation and noise can degrade the estimation performance. In this paper, we propose a novel iterative stochastic maximum likelihood (ML) algorithm for DOA estimation of multiple sound sources in the presence of spatially nonuniform noise in the SH domain. The main idea of the proposed algorithm is considering the general model of the received signal in the SH domain. We reduce the complexity of the ML estimation by breaking it down to two separate problems: noise parameters and DOA estimation problems. Simulation results indicate that the proposed algorithm improves the robustness of estimation, i.e, the root mean square error, by at least 7dB compared to the recent methods in the reverberant and noisy environments.