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Noise Suppression for GPR Data Based on SVD of Window-Length-Optimized Hankel Matrix

Ground-penetrating radar (GPR) is an effective tool for subsurface detection. Due to the influence of the environment and equipment, the echoes of GPR contain significant noise. In order to suppress noise for GPR data, a method based on singular value decomposition (SVD) of a window-length-optimized...

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Detalles Bibliográficos
Autores principales: Xue, Wei, Luo, Yan, Yang, Yue, Huang, Yujin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6749384/
https://www.ncbi.nlm.nih.gov/pubmed/31484410
http://dx.doi.org/10.3390/s19173807
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author Xue, Wei
Luo, Yan
Yang, Yue
Huang, Yujin
author_facet Xue, Wei
Luo, Yan
Yang, Yue
Huang, Yujin
author_sort Xue, Wei
collection PubMed
description Ground-penetrating radar (GPR) is an effective tool for subsurface detection. Due to the influence of the environment and equipment, the echoes of GPR contain significant noise. In order to suppress noise for GPR data, a method based on singular value decomposition (SVD) of a window-length-optimized Hankel matrix is proposed in this paper. First, SVD is applied to decompose the Hankel matrix of the original data, and the fourth root of the fourth central moment of singular values is used to optimize the window length of the Hankel matrix. Then, the difference spectrum of singular values is used to construct a threshold, which is used to distinguish between components of effective signals and components of noise. Finally, the Hankel matrix is reconstructed with singular values corresponding to effective signals to suppress noise, and the denoised data are recovered from the reconstructed Hankel matrix. The effectiveness of the proposed method is verified with both synthetic and field measurements. The experimental results show that the proposed method can effectively improve noise removal performance under different detection scenarios.
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spelling pubmed-67493842019-09-27 Noise Suppression for GPR Data Based on SVD of Window-Length-Optimized Hankel Matrix Xue, Wei Luo, Yan Yang, Yue Huang, Yujin Sensors (Basel) Article Ground-penetrating radar (GPR) is an effective tool for subsurface detection. Due to the influence of the environment and equipment, the echoes of GPR contain significant noise. In order to suppress noise for GPR data, a method based on singular value decomposition (SVD) of a window-length-optimized Hankel matrix is proposed in this paper. First, SVD is applied to decompose the Hankel matrix of the original data, and the fourth root of the fourth central moment of singular values is used to optimize the window length of the Hankel matrix. Then, the difference spectrum of singular values is used to construct a threshold, which is used to distinguish between components of effective signals and components of noise. Finally, the Hankel matrix is reconstructed with singular values corresponding to effective signals to suppress noise, and the denoised data are recovered from the reconstructed Hankel matrix. The effectiveness of the proposed method is verified with both synthetic and field measurements. The experimental results show that the proposed method can effectively improve noise removal performance under different detection scenarios. MDPI 2019-09-03 /pmc/articles/PMC6749384/ /pubmed/31484410 http://dx.doi.org/10.3390/s19173807 Text en © 2019 by 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/).
spellingShingle Article
Xue, Wei
Luo, Yan
Yang, Yue
Huang, Yujin
Noise Suppression for GPR Data Based on SVD of Window-Length-Optimized Hankel Matrix
title Noise Suppression for GPR Data Based on SVD of Window-Length-Optimized Hankel Matrix
title_full Noise Suppression for GPR Data Based on SVD of Window-Length-Optimized Hankel Matrix
title_fullStr Noise Suppression for GPR Data Based on SVD of Window-Length-Optimized Hankel Matrix
title_full_unstemmed Noise Suppression for GPR Data Based on SVD of Window-Length-Optimized Hankel Matrix
title_short Noise Suppression for GPR Data Based on SVD of Window-Length-Optimized Hankel Matrix
title_sort noise suppression for gpr data based on svd of window-length-optimized hankel matrix
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6749384/
https://www.ncbi.nlm.nih.gov/pubmed/31484410
http://dx.doi.org/10.3390/s19173807
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