Aktaş, Metin and Özkan, Hüseyin (2018) Acoustic direction finding using single acoustic vector sensor under high reverberation. Digital Signal Processing, 75 . pp. 56-70. ISSN 1051-2004 (Print) 1095-4333 (Online)
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Official URL: http://dx.doi.org/10.1016/j.dsp.2018.01.001
Abstract
We propose a novel and robust method for acoustic direction finding, which is solely based on acoustic pressure and pressure gradient measurements from single Acoustic Vector Sensor (AVS). We do not make any stochastic and sparseness assumptions regarding the signal source and the environmental characteristics. Hence, our method can be applied to a wide range of wideband acoustic signals including the speech and noise-like signals in various environments. Our method identifies the “clean” time frequency bins that are not distorted by multipath signals and noise, and estimates the 2D-DOA angles at only those identified bins. Moreover, the identification of the clean bins and the corresponding DOA estimation are performed jointly in one framework in a computationally highly efficient manner. We mathematically and experimentally show that the false detection rate of the proposed method is zero, i.e., none of the time-frequency bins with multiple sources are wrongly labeled as single-source, when the source directions do not coincide. Therefore, our method is significantly more reliable and robust compared to the competing state-of-the-art methods that perform the time-frequency bin selection and the DOA estimation separately. The proposed method, for performed simulations, estimates the source direction with high accuracy (less than 1 degree error) even under significantly high reverberation conditions.
Item Type: | Article |
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Uncontrolled Keywords: | Acoustic vector sensor; Direction of arrival estimation; Source localization; Under-determined; High reverberation; Time-frequency analysis |
Subjects: | T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK5101-6720 Telecommunication |
Divisions: | Faculty of Engineering and Natural Sciences > Academic programs > Telecommunications Faculty of Engineering and Natural Sciences |
Depositing User: | Hüseyin Özkan |
Date Deposited: | 08 Aug 2018 21:25 |
Last Modified: | 15 Jun 2023 14:46 |
URI: | https://research.sabanciuniv.edu/id/eprint/35500 |