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This paper introduces a method to estimate the direction of arrival of an acoustic signal based on finding maximum power in iteratively reduced regions of a spherical surface. A plane wave decomposition beamformer is used to produce power estimates at sparsely distributed points on the sphere. Iterating beam orientation based on the orientation of maximum energy produces accurate localization results. The method is tested using varying reverberation times, source-receiver distances, and angular separation of multiple sources and compared against a pseudo-intensity vector estimator. Results demonstrate that this method is suitable for integration into real-time telematic frameworks, especially in reverberant conditions.
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Sparse Iterative Beamforming Using Spherical Microphone Arrays for Low-Latency Direction of Arrival Estimation in Reverberant Environments
Acoustic direction of arrival estimation methods allows positional information about sound sources to be transmitted over a network using minimal bandwidth. For these purposes,methods that prioritize low computational overhead and consistent accuracy under non-ideal conditions are preferred. The estimation method introduced in this paper uses a set of steered beams to estimate directional energy at sparsely distributed orientations around a spherical microphone array. By iteratively adjusting beam orientations based on the orientation of maximum energy, an accurate orientation estimate of a sound source may be produced with minimal computational cost. Incorporating conditions based on temporal smoothing and diffuse energy estimation further refines this process. Testing under simulated conditions indicates favorable accuracy under reverberation and source discrimination when compared with several other contemporary localization methods. Outcomes include an average localization error of less than 10◦ under 2 s of reverberation time (T60) and the potential to separate up to four sound sources under the same conditions. Results from testing in a laboratory environment demonstrate potential for integration into real-time frameworks.
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- Award ID(s):
- 1909229
- PAR ID:
- 10324140
- Date Published:
- Journal Name:
- Journal of the Audio Engineering Society
- Volume:
- 69
- Issue:
- 12
- ISSN:
- 1549-4950
- Page Range / eLocation ID:
- 967-977
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/https://doi.org/10.17743/jaes.2021.0057
