Coarray Manifold Separation In The Spherical Harmonics Domain For Enhanced Source Localization
Shekhar Kumar Yadav, Nithin V. George · ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) · 2022
The order of a three-dimensional wavefield captured by a spherical array is limited by the number of sampling points i.e. the number of sensors in the array. This restricts the source localization performance of existing techniques for a spherical array. In this paper, we introduce the concept of difference coarray to spherical arrays and propose an algorithm which utilises the increased degrees-of-freedom (DOF) provided by the virtual coarray sensors to perform enhanced source localization. We make use of coarray manifold separation in the spherical harmonics domain to generate a Vandermonde structured coarray manifold matrix which allows us to propose a novel subspace-based algorithm, which we call the coarraySH-MUSIC. We also introduce a polynomial rooting version of our algorithm which does not rely on extensive grid searches. The proposed algorithms are evaluated using various simulated experiments on source localization.