A 3D sound source localization (SSL) technique for multiple spherical arrays is proposed. Spherical arrays have been popularly used for direction of arrival (DoA) estimation, which serves as important prior knowledge for source separation, dereverberation, and binaural rendering for VR applications. In this work, a parametric 3D SSL technique is proposed that can detect multiple sources using multiple spherical array recordings. From the enriched information by using multiple arrays, we show that the parametric estimation of 3D positions is possible without scanning candidate positions in 3D space. To mitigate the problem of the ambiguous association between DoAs estimated from different arrays, a total covariance matrix including both auto- and cross-covariance matrices between arrays is utilized such that DoAs from arrays are automatically paired to uniquely localize 3D source positions. The joint parameter estimation is based on the generalized joint Schur decomposition of multiple matrices combined with a geometric projection robustly guiding the convergence of the proposed iteration algorithm. Simulations conducted in anechoic and reverberant room conditions reveal that the proposed technique can accurately determine multiple source positions in 3D space without ambiguities.

The estimation of direction of arrivals (DoAs) from spherical microphone array data is one of the key issues in extracting source information from all-around audio recordings. One such technique is the eigenbeam estimation of signal parameters via the rotational invariance technique (EB-ESPRIT), which separates the signal subspace related to the stationary sound field and then directly estimates DoAs of multiple sound sources. EB-ESPRIT has been evolved in many different ways by involving different types of recurrence relations of spherical harmonics, all of which are able to identify DoAs of a limited number of sources that are noticeably smaller than the number of finite-order spherical harmonic coefficients recorded. In this work, we report that it is possible to go beyond the known limits of detectable sources. The proposed formula is also based on conventional recurrence relations and probably permits to reach the ultimate limit by additional constraints of the signal parameters that can better exploit the highest-order coefficients. Monte-Carlo simulations conducted with various source positions and signal-to-noise ratios (SNRs) reveal that the proposed technique can detect more sources with insignificant loss in estimation performance and robustness.

This paper reviews the current state of loudspeaker-based spatial sound reproduction methods from technical perspective as well as perceptual perspective. A nomenclature is developed that allows for a strict separation between these two perspectives. The physical fundamentals, practical realization, and results from perceptual studies are discussed for a number of well-established and emerging reproduction techniques. Further, the paper outlines novel approaches to spatial sound evaluation in terms of perceived quality and provides a comparison of current approaches.