Automated detection and tracking of hyperbolic diffractions applied to engineering GPR data sets

Abstract

PreviousNext No Access19th International Conference on Ground Penetrating RadarAutomated detection and tracking of hyperbolic diffractions applied to engineering GPR data setsAuthors: Matteo DossiEmanuele ForteBarbara CosciottiSebastian Emanuel LauroElisabetta MatteiElena PettinelliMichele PipanMatteo DossiRoma Tre UniversitySearch for more papers by this author, Emanuele ForteUniversity of TriesteSearch for more papers by this author, Barbara CosciottiRoma Tre UniversitySearch for more papers by this author, Sebastian Emanuel LauroRoma Tre UniversitySearch for more papers by this author, Elisabetta MatteiRoma Tre UniversitySearch for more papers by this author, Elena PettinelliRoma Tre UniversitySearch for more papers by this author, and Michele PipanUniversity of TriesteSearch for more papers by this authorhttps://doi.org/10.1190/gpr2022-017.1 SectionsAboutPDF/ePub ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinked InRedditEmail Abstract We developed an algorithm to automatically detect and track hyperbolic diffractions within GPR data sets. The procedure uses the apexes as initial seeds, and also pre-estimates the widths of their hyperbolas, thus producing a more objective search window that is automatically adapted to local conditions. Within the search window, hyperbolas with varying EM velocities are fitted to the signal phases surrounding the initial seed, which are then connected to form preliminary hyperbolic paths. Among these paths, the algorithm selects the best fit by assessing several attributes, while possible false positives and redundant hyperbolas are subsequently removed. The proposed procedure can be applied with minimal signal processing, and it requires only limited input from the interpreter. The algorithm was able to accurately track most diffractions within engineering GPR data sets, with very few false positives and negatives. Keywords: edge detection, GPR, algorithm, attributes, signal processingPermalink: https://doi.org/10.1190/gpr2022-017.1FiguresReferencesRelatedDetails 19th International Conference on Ground Penetrating RadarISSN (online):2159-6832Copyright: 2022 Pages: 166 publication data© 2022 Published in electronic format with permission by the Society of Exploration GeophysicistsPublisher:Society of Exploration Geophysicists HistoryPublished Online: 13 Oct 2022 CITATION INFORMATION Matteo Dossi, Emanuele Forte, Barbara Cosciotti, Sebastian Emanuel Lauro, Elisabetta Mattei, Elena Pettinelli, and Michele Pipan, (2022), "Automated detection and tracking of hyperbolic diffractions applied to engineering GPR data sets," SEG Global Meeting Abstracts : 127-130. https://doi.org/10.1190/gpr2022-017.1 Plain-Language Summary Keywordsedge detectionGPRalgorithmattributessignal processingPDF DownloadLoading ...