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Open AccessCommunication

Towards Robust Multiple Blind Source Localization Using Source Separation and Beamforming

by 1,†, 2,†, 1,*, 1, 3 and 2
1
School of Electronic Information and Engineering, Huazhong University of Science and Technology, Wuhan 430074, China
2
School of Computer Science and Engineering, Nanyang Technological University, Singapore 639798, Singapore
3
Department of Computing and Software, McMaster University, Hamilton, ON L8S 4L8, Canada
*
Author to whom correspondence should be addressed.
These authors contributed equally to this work.
Sensors 2021, 21(2), 532; https://doi.org/10.3390/s21020532
Received: 8 December 2020 / Revised: 10 January 2021 / Accepted: 11 January 2021 / Published: 13 January 2021
(This article belongs to the Section Intelligent Sensors)
Multiple blind sound source localization is the key technology for a myriad of applications such as robotic navigation and indoor localization. However, existing solutions can only locate a few sound sources simultaneously due to the limitation imposed by the number of microphones in an array. To this end, this paper proposes a novel multiple blind sound source localization algorithms using Source seParation and BeamForming (SPBF). Our algorithm overcomes the limitations of existing solutions and can locate more blind sources than the number of microphones in an array. Specifically, we propose a novel microphone layout, enabling salient multiple source separation while still preserving their arrival time information. After then, we perform source localization via beamforming using each demixed source. Such a design allows minimizing mutual interference from different sound sources, thereby enabling finer AoA estimation. To further enhance localization performance, we design a new spectral weighting function that can enhance the signal-to-noise-ratio, allowing a relatively narrow beam and thus finer angle of arrival estimation. Simulation experiments under typical indoor situations demonstrate a maximum of only 4 even under up to 14 sources. View Full-Text
Keywords: microphone array layout; source separation; beamforming microphone array layout; source separation; beamforming
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MDPI and ACS Style

Pu, H.; Cai, C.; Hu, M.; Deng, T.; Zheng, R.; Luo, J. Towards Robust Multiple Blind Source Localization Using Source Separation and Beamforming. Sensors 2021, 21, 532. https://doi.org/10.3390/s21020532

AMA Style

Pu H, Cai C, Hu M, Deng T, Zheng R, Luo J. Towards Robust Multiple Blind Source Localization Using Source Separation and Beamforming. Sensors. 2021; 21(2):532. https://doi.org/10.3390/s21020532

Chicago/Turabian Style

Pu, Henglin; Cai, Chao; Hu, Menglan; Deng, Tianping; Zheng, Rong; Luo, Jun. 2021. "Towards Robust Multiple Blind Source Localization Using Source Separation and Beamforming" Sensors 21, no. 2: 532. https://doi.org/10.3390/s21020532

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