Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/147568
Title: Towards robust multiple blind source localization using source separation and beamforming
Authors: Pu, Henglin
Cai, Chao
Hu, Menglan
Deng, Tianping
Zheng, Rong
Luo, Jun
Keywords: Engineering::Computer science and engineering
Issue Date: 2021
Source: Pu, H., Cai, C., Hu, M., Deng, T., Zheng, R. & Luo, J. (2021). Towards robust multiple blind source localization using source separation and beamforming. Sensors, 21(2). https://dx.doi.org/10.3390/s21020532
Journal: Sensors 
Abstract: 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.
URI: https://hdl.handle.net/10356/147568
ISSN: 1424-8220
DOI: 10.3390/s21020532
Schools: School of Computer Science and Engineering 
Rights: © 2021 The Authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:SCSE Journal Articles

Files in This Item:
File Description SizeFormat 
sensors-21-00532.pdf809.82 kBAdobe PDFThumbnail
View/Open

SCOPUSTM   
Citations 20

10
Updated on Mar 24, 2024

Web of ScienceTM
Citations 20

6
Updated on Oct 29, 2023

Page view(s)

245
Updated on Mar 28, 2024

Download(s) 50

63
Updated on Mar 28, 2024

Google ScholarTM

Check

Altmetric


Plumx

Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.