Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/6425
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dc.contributor.authorGürbüz, Ali Cafer-
dc.contributor.authorMcClellan, James H.-
dc.contributor.authorScott, Waymond R., Jr.-
dc.date.accessioned2021-09-11T15:36:26Z-
dc.date.available2021-09-11T15:36:26Z-
dc.date.issued2012en_US
dc.identifier.issn1051-2004-
dc.identifier.issn1095-4333-
dc.identifier.urihttps://doi.org/10.1016/j.dsp.2010.11.003-
dc.identifier.urihttps://hdl.handle.net/20.500.11851/6425-
dc.description.abstractFeature detection in sensing problems usually involves two processing stages. First, the raw data collected by a sensor, such as a Ground Penetrating Radar (GPR), is inverted to form an image of the subsurface area. Second, the image is searched for features like lines using an algorithm such as the Hough Transform (HT), which converts the problem of finding spatially spread patterns in the image space to detecting sparse peaks in the HT parameter space. This paper exploits the sparsity of features to combine the two stages into one direct processing step using Compressive Sensing (CS). The CS framework finds the HT parameters directly from the raw sensor measurements without having to construct an image of the sensed media. In addition to skipping the image formation step, CS processing can be done with a minimal number of raw sensor measurements, which decreases the data acquisition cost. The utility of this CS-based method is demonstrated for finding buried linear structures in both simulated and experimental GPR data. (C) 2010 Elsevier Inc. All rights reserved.en_US
dc.description.sponsorshipARO-MURIMURI [DAAD19-02-1-0252]en_US
dc.description.sponsorshipThis work supported by an ARO-MURI grant: "Multi-Modal Inverse Scattering for Detection and Classification of General Concealed Targets", under contract number DAAD19-02-1-0252.en_US
dc.language.isoenen_US
dc.publisherAcademic Press Inc Elsevier Scienceen_US
dc.relation.ispartofDigital Signal Processingen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectCompressed sensingen_US
dc.subjectLine detectionen_US
dc.subjectGPRen_US
dc.subjectSubsurface imagingen_US
dc.subjectCompressive feature extractionen_US
dc.titleCompressive Sensing of Underground Structures Using Gpren_US
dc.typeArticleen_US
dc.departmentFaculties, Faculty of Engineering, Department of Electrical and Electronics Engineeringen_US
dc.departmentFakülteler, Mühendislik Fakültesi, Elektrik ve Elektronik Mühendisliği Bölümütr_TR
dc.identifier.volume22en_US
dc.identifier.issue1en_US
dc.identifier.startpage66en_US
dc.identifier.endpage73en_US
dc.authorid0000-0001-8923-0299-
dc.authorid0000-0001-8923-0299-
dc.identifier.wosWOS:000297663200006en_US
dc.identifier.scopus2-s2.0-81555207188en_US
dc.institutionauthorGürbüz, Ali Cafer-
dc.identifier.doi10.1016/j.dsp.2010.11.003-
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.identifier.scopusqualityQ1-
item.openairetypeArticle-
item.languageiso639-1en-
item.grantfulltextnone-
item.fulltextNo Fulltext-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.cerifentitytypePublications-
Appears in Collections:Elektrik ve Elektronik Mühendisliği Bölümü / Department of Electrical & Electronics Engineering
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection
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