{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,28]],"date-time":"2026-03-28T06:28:40Z","timestamp":1774679320436,"version":"3.50.1"},"reference-count":62,"publisher":"MDPI AG","issue":"11","license":[{"start":{"date-parts":[[2023,6,1]],"date-time":"2023-06-01T00:00:00Z","timestamp":1685577600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001868","name":"National Science Council of Taiwan, ROC","doi-asserted-by":"publisher","award":["NSC 100-2116-M-003-005"],"award-info":[{"award-number":["NSC 100-2116-M-003-005"]}],"id":[{"id":"10.13039\/501100001868","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Numerous data processing algorithms are available for ground-penetrating radar (GPR) data processing. However, most of the existing processing algorithms are derived from Fourier theory and assume that the system is linear or that data are stationary, which may oversimplify the case. Some nonlinear algorithms are accessible for improvement but generally are for stationary and deterministic systems. To alleviate the dilemma, this study proposes an algorithm fusion scheme that employs standard linear techniques in conjunction with a newer nonlinear and non-stationary method. The linear techniques include linear filtering, migration, and interpolation. The newer method is mainly for nonlinear filtering and image reconstruction. The results can be demonstrated in a two-dimensional single profile (time\u2013distance section) or a 3D visualization if survey lines fulfill the 3D Nyquist sample intervals requirement. Two controlled experiments were conducted to justify the proposed scheme. Then, a field study including two examples was carried out to demonstrate the feasibility of practical applications. Compared with conventional methods, the proposed algorithm fusion provides better visualization and integrative interpretation for GPR imaging.<\/jats:p>","DOI":"10.3390\/rs15112886","type":"journal-article","created":{"date-parts":[[2023,6,2]],"date-time":"2023-06-02T01:33:54Z","timestamp":1685669634000},"page":"2886","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Algorithm Fusion for 3D Ground-Penetrating Radar Imaging with Field Examples"],"prefix":"10.3390","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4409-7639","authenticated-orcid":false,"given":"Yih","family":"Jeng","sequence":"first","affiliation":[{"name":"Department of Earth Sciences, National Taiwan Normal University, 88, Sec. 4, Ting-Chou Road, Taipei 116, Taiwan"}]},{"given":"Hung-Ming","family":"Yu","sequence":"additional","affiliation":[{"name":"New Taipei Municipal SanMin High School, New Taipei City 247, Taiwan"}]},{"given":"Chih-Sung","family":"Chen","sequence":"additional","affiliation":[{"name":"National Lo-Dong Senior High School, Yilan 265, Taiwan"}]}],"member":"1968","published-online":{"date-parts":[[2023,6,1]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"531","DOI":"10.1111\/j.1365-2478.1989.tb02221.x","article-title":"Ground-penetrating radar for high resolution mapping of soil and rock stratigraphy","volume":"3","author":"Davis","year":"1989","journal-title":"Geophys. 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