Towards robust multiple blind source localization using source separation and beamforming
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 th...
| Main Authors: | , , , , , |
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| Other Authors: | |
| Format: | Journal Article |
| Language: | English |
| Published: |
2021
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10356/147568 |
| _version_ | 1826119841988214784 |
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| author | Pu, Henglin Cai, Chao Hu, Menglan Deng, Tianping Zheng, Rong Luo, Jun |
| author2 | School of Computer Science and Engineering |
| author_facet | School of Computer Science and Engineering Pu, Henglin Cai, Chao Hu, Menglan Deng, Tianping Zheng, Rong Luo, Jun |
| author_sort | Pu, Henglin |
| collection | NTU |
| description | 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. |
| first_indexed | 2024-10-01T05:06:43Z |
| format | Journal Article |
| id | ntu-10356/147568 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T05:06:43Z |
| publishDate | 2021 |
| record_format | dspace |
| spelling | ntu-10356/1475682021-04-06T06:03:11Z Towards robust multiple blind source localization using source separation and beamforming Pu, Henglin Cai, Chao Hu, Menglan Deng, Tianping Zheng, Rong Luo, Jun School of Computer Science and Engineering Engineering::Computer science and engineering Microphone Array Layout Source Separation 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. Published version 2021-04-06T06:03:11Z 2021-04-06T06:03:11Z 2021 Journal Article 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 1424-8220 https://hdl.handle.net/10356/147568 10.3390/s21020532 33450995 2-s2.0-85099394886 2 21 en Sensors © 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/). application/pdf |
| spellingShingle | Engineering::Computer science and engineering Microphone Array Layout Source Separation Pu, Henglin Cai, Chao Hu, Menglan Deng, Tianping Zheng, Rong Luo, Jun Towards robust multiple blind source localization using source separation and beamforming |
| title | Towards robust multiple blind source localization using source separation and beamforming |
| title_full | Towards robust multiple blind source localization using source separation and beamforming |
| title_fullStr | Towards robust multiple blind source localization using source separation and beamforming |
| title_full_unstemmed | Towards robust multiple blind source localization using source separation and beamforming |
| title_short | Towards robust multiple blind source localization using source separation and beamforming |
| title_sort | towards robust multiple blind source localization using source separation and beamforming |
| topic | Engineering::Computer science and engineering Microphone Array Layout Source Separation |
| url | https://hdl.handle.net/10356/147568 |
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