Evaluation of Sparse Acoustic Array Geometries for the Application in Indoor Localization
arxiv(2024)
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 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.
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