{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,6]],"date-time":"2026-07-06T10:38:48Z","timestamp":1783334328120,"version":"3.54.6"},"reference-count":15,"publisher":"MDPI AG","issue":"10","license":[{"start":{"date-parts":[[2018,10,12]],"date-time":"2018-10-12T00:00:00Z","timestamp":1539302400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"Natural Science Foundation of China","doi-asserted-by":"publisher","award":["41774124"],"award-info":[{"award-number":["41774124"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Ground-penetrating radar (GPR) is a kind of high-frequency electromagnetic detection technology. It is mainly used to locate targets and interfaces in underground structures. In addition to the effective signals reflected from the subsurface objects or interfaces, the GPR signals in field work also include noise and different clutters, such as antenna-coupled waves, ground clutters, and radio-frequency interference, which have similar wavelet spectral characteristics with the target signals. Clutter and noise seriously interfere with the target\u2019s response signal. The singular value decomposition (SVD) filtering method can select appropriate singular values and characteristic components corresponding to the effective signals for signal reconstruction to filter the GPR data. However, the conventional time-domain SVD method introduces fake signals when eliminating direct waves, and does not have good suppression of random noise around non-horizontal phase axes. Here, an SVD method based on the Hankel matrix in the local frequency domain of GPR data is proposed. Different numerical models and real field GPR data were handled using the proposed method. Based on the power of fake signals introduced via different processes, qualitative and quantitative analyses were carried out. The comparison shows that the newly proposed method could improve efforts to suppress random noise around non-horizontal phase reflection events and weaken the horizontal fake signals introduced by eliminating clutter such as ground waves.<\/jats:p>","DOI":"10.3390\/s18103422","type":"journal-article","created":{"date-parts":[[2018,10,12]],"date-time":"2018-10-12T10:54:03Z","timestamp":1539341643000},"page":"3422","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":41,"title":["Clutter Elimination and Random-Noise Denoising of GPR Signals Using an SVD Method Based on the Hankel Matrix in the Local Frequency Domain"],"prefix":"10.3390","volume":"18","author":[{"given":"Wenda","family":"Bi","sequence":"first","affiliation":[{"name":"School of Ocean and Earth Science, Tongji University, Shanghai 200092, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8120-6435","authenticated-orcid":false,"given":"Yonghui","family":"Zhao","sequence":"additional","affiliation":[{"name":"School of Ocean and Earth Science, Tongji University, Shanghai 200092, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Cong","family":"An","sequence":"additional","affiliation":[{"name":"School of Ocean and Earth Science, Tongji University, Shanghai 200092, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shufan","family":"Hu","sequence":"additional","affiliation":[{"name":"School of Ocean and Earth Science, Tongji University, Shanghai 200092, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2018,10,12]]},"reference":[{"key":"ref_1","unstructured":"Jol, H. (2009). Ground Penetrating Radar: Theory and Applications, Elsevier Science."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Liu, T., Zhu, Y., and Su, Y. (2018). Method for Compensating Signal Attenuation Using Stepped-Frequency Ground Penetrating Radar. Sensors, 18.","DOI":"10.3390\/s18051366"},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Sun, H., Pashoutani, S., and Zhu, J. (2018). Nondestructive Evaluation of Concrete Bridge Decks with Automated Acoustic Scanning System and Ground Penetrating Radar. Sensors, 18.","DOI":"10.3390\/s18061955"},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Pipan, M., Forte, E., and Finetti, I. (2002, January 12). Processing and inversion of multi-offset and multi-azimuth GPR data for environmental and engineering applications. Proceedings of the 9th International Conference on Ground Penetrating Radar, Santa Barbara, CA, USA.","DOI":"10.1117\/12.462273"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"11","DOI":"10.1016\/j.jappgeo.2018.04.018","article-title":"Underwater archaeological investigation using ground penetrating radar: A case analysis of Shanglinhu Yue Kiln sites (China)","volume":"154","author":"Qin","year":"2018","journal-title":"J. Appl. Geophys."},{"key":"ref_6","unstructured":"Abujarad, F., Nadim, G., and Omar, A. (2005, January 2\u20133). Clutter reduction and detection of landmine objects in ground penetrating radar data using singular value decomposition (SVD). Proceedings of the 3rd International Workshop on Advanced Ground Penetrating Radar, Delft, The Netherlands."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"347","DOI":"10.1088\/1742-2140\/aa8cb4","article-title":"GPR random noise reduction using BPD and EMD","volume":"15","author":"Ostori","year":"2018","journal-title":"J. Geophys. Eng."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"2","DOI":"10.1080\/07468342.1996.11973744","article-title":"A Singularly Valuable Decomposition: The SVD of a Matrix","volume":"27","author":"Dan","year":"1996","journal-title":"Coll. Math. J."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"200","DOI":"10.1109\/LGRS.2009.2031657","article-title":"Reconstruction of GPR Signals by Spectral Analysis of the SVD Components of the Data Matrix","volume":"7","author":"Nan","year":"2010","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Riaz, M.M., and Ghafoor, A. (2013, January 19\u201323). Ground penetrating radar image enhancement using singular value decomposition. Proceedings of the IEEE International Symposium on Circuits and Systems, Beijing, China.","DOI":"10.1109\/ISCAS.2013.6572359"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"1635","DOI":"10.1109\/TGRS.2012.2207906","article-title":"Optimized SVD Approach for the Detection of Weak Subsurface Targets from Ground-Penetrating Radar Data","volume":"51","author":"Grzegorczyk","year":"2013","journal-title":"IEEE Geosci. Remote Sens. Soc."},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Song, C., Lu, Q., Liu, C., and Gao, Y. (2016, January 13\u201316). Random noise de-noising and direct wave eliminating in ground penetrating radar signal using SVD method. Proceedings of the 16th International Conference on Ground Penetrating Radar (GPR), Hong Kong, China.","DOI":"10.1109\/ICGPR.2016.7572636"},{"key":"ref_13","first-page":"259","article-title":"Research on Adaptive noise elimination of ground penetrating radar data by singular value decomposition method","volume":"S","author":"Chen","year":"2017","journal-title":"Geotech. Investig. Surv."},{"key":"ref_14","first-page":"202","article-title":"Local SVD for random noise suppression of seismic data in frequency domain","volume":"47","author":"Liu","year":"2012","journal-title":"Oil Geophys. Prospect."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"163","DOI":"10.1016\/j.cpc.2016.08.020","article-title":"gprMax: Open source software to simulate electromagnetic wave propagation for Ground Penetrating Radar","volume":"209","author":"Warren","year":"2016","journal-title":"Comput. Phys. Commun."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/18\/10\/3422\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T15:25:14Z","timestamp":1760196314000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/18\/10\/3422"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,10,12]]},"references-count":15,"journal-issue":{"issue":"10","published-online":{"date-parts":[[2018,10]]}},"alternative-id":["s18103422"],"URL":"https:\/\/doi.org\/10.3390\/s18103422","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2018,10,12]]}}}