{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,21]],"date-time":"2026-03-21T19:28:43Z","timestamp":1774121323402,"version":"3.50.1"},"reference-count":37,"publisher":"MDPI AG","issue":"11","license":[{"start":{"date-parts":[[2022,5,26]],"date-time":"2022-05-26T00:00:00Z","timestamp":1653523200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Several researchers have utilized multipath summation to manage the common problem of scattered energy within GPR sections. Such energy results in degrading the lateral resolution and continuity of reflectors. If detailed velocity models are known, then it is fairly easy to focus the scattered energy by means of conventional migration methods. However, this is rarely the case in GPR sections, as the common-offset antenna array is mostly used, and therefore cannot provide velocity models. This gives an important advantage for the multipath summation method, which has proved to be successful in focusing such diffractions, without the need to build a detailed migration velocity field model. This multipath summation method is based on stacking (summation) of constant velocity migrated sections (weighted or not) over a predefined velocity range. The main drawback of this technique is the high computational cost and the need for user interference to select the appropriate stacking weights. We developed an improved implementation of the weighted multipath summation method that reduces both the computational cost, and the user interference in stacking weights selections. This data adaptive methodology can expedite the migration process, suppress the need for a detailed velocity model, and reduce the user subjectivity. Moreover, a data adaptive spectral scaling scheme was developed. This is applied on the output of the multipath summation process to reduce the expected blurriness in the resulting GPR sections.<\/jats:p>","DOI":"10.3390\/rs14112547","type":"journal-article","created":{"date-parts":[[2022,5,31]],"date-time":"2022-05-31T00:25:12Z","timestamp":1653956712000},"page":"2547","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["A New Approach for Adaptive GPR Diffraction Focusing"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6672-6205","authenticated-orcid":false,"given":"Hamdan","family":"Hamdan","sequence":"first","affiliation":[{"name":"Petroleum Geosciences and Remote Sensing Program, Department of Applied Physics and Astronomy, University of Sharjah, Sharjah P.O. Box 27272, United Arab Emirates"}]},{"given":"Nikos","family":"Economou","sequence":"additional","affiliation":[{"name":"Applied Geophysics Lab, School of Mineral Resources Engineering, Technical University of Crete, 731 00 Chania, Greece"},{"name":"Earth Science Department, Sultan Qaboos University, Muscat 123, Oman"}]},{"given":"Antonis","family":"Vafidis","sequence":"additional","affiliation":[{"name":"Applied Geophysics Lab, School of Mineral Resources Engineering, Technical University of Crete, 731 00 Chania, Greece"}]},{"given":"Maksim","family":"Bano","sequence":"additional","affiliation":[{"name":"ITES UMR-7063, EOST, University of Strasbourg, F-67000 Strasbourg, France"}]},{"given":"Jose","family":"Ortega-Ramirez","sequence":"additional","affiliation":[{"name":"Laboratorio de Geof\u00edsica, Instituto Nacional de Antropologia e Historia, Mexico City 06060, Mexico"}]}],"member":"1968","published-online":{"date-parts":[[2022,5,26]]},"reference":[{"key":"ref_1","first-page":"280738","article-title":"A review on migration methods in B-Scan Ground penetrating radar imaging","volume":"2014","author":"Demirci","year":"2014","journal-title":"Math. 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