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Steered sample algorithm for acoustic source localization
High-precision source localization depends on many factors, including a suitable location method. Beamforming-based methods, such as the steered response power (SRP), are a common type of acoustic localization methods. However, these methods have low spatial resolution. The SRP method with phase tra...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7588096/ https://www.ncbi.nlm.nih.gov/pubmed/33105477 http://dx.doi.org/10.1371/journal.pone.0241129 |
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author | Liu, Bin Zhang, Lichao Nie, Pengfei Han, Xingcheng Han, Yan |
author_facet | Liu, Bin Zhang, Lichao Nie, Pengfei Han, Xingcheng Han, Yan |
author_sort | Liu, Bin |
collection | PubMed |
description | High-precision source localization depends on many factors, including a suitable location method. Beamforming-based methods, such as the steered response power (SRP), are a common type of acoustic localization methods. However, these methods have low spatial resolution. The SRP method with phase transform (SRP-PHAT) improves the spatial resolution of SRP and is one of the most effective and robust methods for source localization. However, the introduction of a phase transform to SRP might amplify the power of the noise and result in many local extrema in the SRP space, which has a negative impact on source localization. In this paper, a steered sample algorithm (SSA) based on the reciprocity of wave propagation for acoustic source localization is proposed. The SSA localization process is similar to the hyperbolic Radon transform, which is theoretically analyzed and is the most essential difference form the SRP/SRP-PHAT. Compared with the SRP-PHAT, the experimental results demonstrate that the SSA perform better when it comes to array signal positioning with limited array elements and narrow azimuth signal, where SSA can achieve high precision positioning with lower SNR. |
format | Online Article Text |
id | pubmed-7588096 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-75880962020-10-30 Steered sample algorithm for acoustic source localization Liu, Bin Zhang, Lichao Nie, Pengfei Han, Xingcheng Han, Yan PLoS One Research Article High-precision source localization depends on many factors, including a suitable location method. Beamforming-based methods, such as the steered response power (SRP), are a common type of acoustic localization methods. However, these methods have low spatial resolution. The SRP method with phase transform (SRP-PHAT) improves the spatial resolution of SRP and is one of the most effective and robust methods for source localization. However, the introduction of a phase transform to SRP might amplify the power of the noise and result in many local extrema in the SRP space, which has a negative impact on source localization. In this paper, a steered sample algorithm (SSA) based on the reciprocity of wave propagation for acoustic source localization is proposed. The SSA localization process is similar to the hyperbolic Radon transform, which is theoretically analyzed and is the most essential difference form the SRP/SRP-PHAT. Compared with the SRP-PHAT, the experimental results demonstrate that the SSA perform better when it comes to array signal positioning with limited array elements and narrow azimuth signal, where SSA can achieve high precision positioning with lower SNR. Public Library of Science 2020-10-26 /pmc/articles/PMC7588096/ /pubmed/33105477 http://dx.doi.org/10.1371/journal.pone.0241129 Text en © 2020 Liu et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Liu, Bin Zhang, Lichao Nie, Pengfei Han, Xingcheng Han, Yan Steered sample algorithm for acoustic source localization |
title | Steered sample algorithm for acoustic source localization |
title_full | Steered sample algorithm for acoustic source localization |
title_fullStr | Steered sample algorithm for acoustic source localization |
title_full_unstemmed | Steered sample algorithm for acoustic source localization |
title_short | Steered sample algorithm for acoustic source localization |
title_sort | steered sample algorithm for acoustic source localization |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7588096/ https://www.ncbi.nlm.nih.gov/pubmed/33105477 http://dx.doi.org/10.1371/journal.pone.0241129 |
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