# Acoustic source localization in the spherical harmonics domain exploiting low-rank approximations

arXiv: https://arxiv.org/abs/2303.08480 · HTML: https://mlsanity.com/paper/2303.08480/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 15 Mar 2023.

## Built on by (most cited first, 2 of 2)

- [Implicit neural representation with physics-informed neural networks for the reconstruction of the early part of room impulse responses](https://mlsanity.com/paper/2306.11509/) (2023)
- [A Physics-Informed Neural Network-Based Approach for the Spatial Upsampling of Spherical Microphone Arrays](https://mlsanity.com/paper/2407.18732/) (2024)

## Abstract (arXiv)

Acoustic signal processing in the spherical harmonics domain (SHD) is an active research area that exploits the signals acquired by higher order microphone arrays. A very important task is that concerning the localization of active sound sources. In this paper, we propose a simple yet effective method to localize prominent acoustic sources in adverse acoustic scenarios. By using a proper normalization and arrangement of the estimated spherical harmonic coefficients, we exploit low-rank approximations to estimate the far field modal directional pattern of the dominant source at each time-frame. The experiments confirm the validity of the proposed approach, with superior performance compared to other recent SHD-based approaches.