Direction of arrival estimation of multiple acoustic sources using a maximum likelihood method in the spherical harmonic domain

Direction of arrival estimation (DOA) of multiple acoustic sources has been used for a wide range of applications, including room geometry inference, source separation and speech enhancement. The beamformer-based and subspace-based methods are most commonly used for spherical microphone arrays; however, the former suffers from spatial resolution limitations, while the later suffers from performance degradation in noisy environment. This letter proposes a multiple source DOA estimation approach based on the maximum likelihood method in the spherical harmonic domain and implements an efficient sequential iterative search of maxima on the cost function in the spherical harmonic domain. The proposed method avoids the division of the spherical Bessel function, which makes it suitable for both rigid-sphere and open-sphere configurations. Simulation results show that the proposed method has a significant superiority over the commonly used frequency smoothing multiple signal classification method. Experiments in a normal listening room and a reverberation room validate the effectiveness of the proposed method.