Evaluation of Sparse Acoustic Array Geometries for Indoor Localization

TL;DR

This paper evaluates various sparse acoustic array geometries for indoor localization, demonstrating their effectiveness in source direction estimation and highlighting promising configurations like Open-Box and Nested arrays.

Contribution

It introduces an experimental platform for assessing sparse array geometries and identifies robust configurations for indoor acoustic source localization.

Findings

Open-Box and Nested arrays are robust geometries.

Array can estimate directions of three sources simultaneously.

Mean spherical error of 1.26 degrees in AoA estimation.

Abstract

Angle-of-Arrival estimation technology, with its potential advantages, emerges as an intriguing choice for indoor localization. Notably, it holds the promise of reducing installation costs. In contrast to ToF/TDoA based systems, AoA-based approaches require a reduced number of nodes for effective localization. This characteristic establishes a trade-off between installation costs and the complexity of hardware and software. Moreover, the appeal of acoustic localization is further heightened by its capacity to provide cost-effective hardware solutions while maintaining a high degree of accuracy. Consequently, acoustic AoA estimation technology stands out as a feasible and compelling option in the field of indoor localization. Sparse arrays additionally have the ability to estimate the DoA of more sources than available sensors by placing sensors in a specific geometry. In this contribution, we introduce a measurement platform designed to evaluate various sparse array geometries experimentally. The acoustic microphone array comprises 64 microphones arranged in an 8x8 grid, following an Uniform Rectangular Array (URA) configuration, with a grid spacing of 8.255 mm. This configuration achieves a spatial Nyquist frequency of approximately 20.8 kHz in the acoustic domain at room temperature. Notably, the array exhibits a mean spherical error of 1.26{\deg} when excluding higher elevation angles. The platform allows for masking sensors to simulate sparse array configurations. We assess four array geometries through simulations and experimental data, identifying the Open-Box and Nested array geometries as robust candidates. Additionally, we demonstrate the array's capability to concurrently estimate the directions of three emitting sources using experimental data, employing waveforms consisting of orthogonal codes.