{"title":"基于小波域SVD的探地雷达数据直接耦合去波","authors":"D. Chen, A. Xiang, S. Xiong, L. Wang, L. Guo","doi":"10.13164/re.2022.0564","DOIUrl":null,"url":null,"abstract":". This paper presents a new algorithm of the singular value decomposition (SVD) in the wavelet domain for ground penetrating radar (GPR) to remove direct coupled waves. In fact, direct coupled waves commonly disturb the reflecting waves from underground targets. Besides, the amplitude and energy of direct coupled waves are large, which reduces the resolution of the images to the targets and ad-versely affects the subsequent image interpretation work. The GPR signal is decomposed into several levels by Wavelet to obtain approximation components and detailed components of each level. The information of targets is contained in big eigenvalues of detail components, while the direct coupled waves are contained in small ones. Therefore, the SVD in the wavelet domain can reduce the misjudgment of effective signals and improve the signal to noise ratio (SNR) of GPR signals. The simulated and field GPR data show that the SVD in the wavelet domain denoising method has better results for direct coupled wave removal than the traditional methods, which validates the effectiveness of the proposed denoising method.","PeriodicalId":54514,"journal":{"name":"Radioengineering","volume":null,"pages":null},"PeriodicalIF":0.5000,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Direct Coupled Wave Removal for GPR Data Based on SVD in the Wavelet Domain\",\"authors\":\"D. Chen, A. Xiang, S. Xiong, L. Wang, L. Guo\",\"doi\":\"10.13164/re.2022.0564\",\"DOIUrl\":null,\"url\":null,\"abstract\":\". This paper presents a new algorithm of the singular value decomposition (SVD) in the wavelet domain for ground penetrating radar (GPR) to remove direct coupled waves. In fact, direct coupled waves commonly disturb the reflecting waves from underground targets. Besides, the amplitude and energy of direct coupled waves are large, which reduces the resolution of the images to the targets and ad-versely affects the subsequent image interpretation work. The GPR signal is decomposed into several levels by Wavelet to obtain approximation components and detailed components of each level. The information of targets is contained in big eigenvalues of detail components, while the direct coupled waves are contained in small ones. Therefore, the SVD in the wavelet domain can reduce the misjudgment of effective signals and improve the signal to noise ratio (SNR) of GPR signals. The simulated and field GPR data show that the SVD in the wavelet domain denoising method has better results for direct coupled wave removal than the traditional methods, which validates the effectiveness of the proposed denoising method.\",\"PeriodicalId\":54514,\"journal\":{\"name\":\"Radioengineering\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.5000,\"publicationDate\":\"2022-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Radioengineering\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://doi.org/10.13164/re.2022.0564\",\"RegionNum\":4,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"ENGINEERING, ELECTRICAL & ELECTRONIC\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Radioengineering","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.13164/re.2022.0564","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
Direct Coupled Wave Removal for GPR Data Based on SVD in the Wavelet Domain
. This paper presents a new algorithm of the singular value decomposition (SVD) in the wavelet domain for ground penetrating radar (GPR) to remove direct coupled waves. In fact, direct coupled waves commonly disturb the reflecting waves from underground targets. Besides, the amplitude and energy of direct coupled waves are large, which reduces the resolution of the images to the targets and ad-versely affects the subsequent image interpretation work. The GPR signal is decomposed into several levels by Wavelet to obtain approximation components and detailed components of each level. The information of targets is contained in big eigenvalues of detail components, while the direct coupled waves are contained in small ones. Therefore, the SVD in the wavelet domain can reduce the misjudgment of effective signals and improve the signal to noise ratio (SNR) of GPR signals. The simulated and field GPR data show that the SVD in the wavelet domain denoising method has better results for direct coupled wave removal than the traditional methods, which validates the effectiveness of the proposed denoising method.
期刊介绍:
Since 1992, the Radioengineering Journal has been publishing original scientific and engineering papers from the area of wireless communication and application of wireless technologies. The submitted papers are expected to deal with electromagnetics (antennas, propagation, microwaves), signals, circuits, optics and related fields.
Each issue of the Radioengineering Journal is started by a feature article. Feature articles are organized by members of the Editorial Board to present the latest development in the selected areas of radio engineering.
The Radioengineering Journal makes a maximum effort to publish submitted papers as quickly as possible. The first round of reviews should be completed within two months. Then, authors are expected to improve their manuscript within one month. If substantial changes are recommended and further reviews are requested by the reviewers, the publication time is prolonged.