R. Abrahamsson, E. Larsson, J. Li, J. Habersat, G. Maksymonko, M. Bradley
{"title":"Elimination of leakage and ground-bounce effects in ground-penetrating radar data","authors":"R. Abrahamsson, E. Larsson, J. Li, J. Habersat, G. Maksymonko, M. Bradley","doi":"10.1109/SSP.2001.955244","DOIUrl":null,"url":null,"abstract":"We address the problem of removing specular ground surface reflections and leakage/cross-talk from downward looking stepped frequency ground-penetrating radar (GPR) data. A new model for the ground-bounce and the leakage/cross-talk is introduced. An algorithm that jointly estimates these effects from collected data is presented. The algorithm has the sound foundation of a nonlinear least squares (LS) fit to the presented model. The minimization is performed in a cyclic manner where one step is a linear LS minimization and the other step is a non-linear LS minimization where the optimum can efficiently be found using, e.g., the chirp-transform algorithm. The results after applying the algorithm to measured GPR data, collected at a US army test range, are also shown.","PeriodicalId":70952,"journal":{"name":"信号处理","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2001-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"信号处理","FirstCategoryId":"1093","ListUrlMain":"https://doi.org/10.1109/SSP.2001.955244","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 9
Abstract
We address the problem of removing specular ground surface reflections and leakage/cross-talk from downward looking stepped frequency ground-penetrating radar (GPR) data. A new model for the ground-bounce and the leakage/cross-talk is introduced. An algorithm that jointly estimates these effects from collected data is presented. The algorithm has the sound foundation of a nonlinear least squares (LS) fit to the presented model. The minimization is performed in a cyclic manner where one step is a linear LS minimization and the other step is a non-linear LS minimization where the optimum can efficiently be found using, e.g., the chirp-transform algorithm. The results after applying the algorithm to measured GPR data, collected at a US army test range, are also shown.
期刊介绍:
Journal of Signal Processing is an academic journal supervised by China Association for Science and Technology and sponsored by China Institute of Electronics. The journal is an academic journal that reflects the latest research results and technological progress in the field of signal processing and related disciplines. It covers academic papers and review articles on new theories, new ideas, and new technologies in the field of signal processing. The journal aims to provide a platform for academic exchanges for scientific researchers and engineering and technical personnel engaged in basic research and applied research in signal processing, thereby promoting the development of information science and technology. At present, the journal has been included in the three major domestic core journal databases "China Science Citation Database (CSCD), China Science and Technology Core Journals (CSTPCD), Chinese Core Journals Overview" and Coaj. It is also included in many foreign databases such as Scopus, CSA, EBSCO host, INSPEC, JST, etc.