F. Quivira, Kristen Fassbender, J. Martinez-Lorenzo, C. Rappaport
{"title":"Feasibility of tunnel detection under rough ground surfaces using Underground Focusing Spotlight Synthetic Aperture Radar","authors":"F. Quivira, Kristen Fassbender, J. Martinez-Lorenzo, C. Rappaport","doi":"10.1109/THS.2010.5654932","DOIUrl":null,"url":null,"abstract":"Detecting and imaging the presence of illicit tunnels in any given volume of soil is occasionaly possible because the air that fills them is materially quite different from anything else underground. The Underground Focusing Spotlight Synthetic Aperture Radar (UF-SL-SAR) concept has been suggested for sub-surface tunnel detection due to its ability to scan large areas of terrain in a short amount of time. This paper explores the feasibility of tunnel detection under rough ground surfaces using an algorithmic implementation of the UF-SL-SAR concept. In particular, detectability is investigated as a function of tunnel depth, ground surface roughness and soil type.","PeriodicalId":106557,"journal":{"name":"2010 IEEE International Conference on Technologies for Homeland Security (HST)","volume":"58 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 IEEE International Conference on Technologies for Homeland Security (HST)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/THS.2010.5654932","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
Detecting and imaging the presence of illicit tunnels in any given volume of soil is occasionaly possible because the air that fills them is materially quite different from anything else underground. The Underground Focusing Spotlight Synthetic Aperture Radar (UF-SL-SAR) concept has been suggested for sub-surface tunnel detection due to its ability to scan large areas of terrain in a short amount of time. This paper explores the feasibility of tunnel detection under rough ground surfaces using an algorithmic implementation of the UF-SL-SAR concept. In particular, detectability is investigated as a function of tunnel depth, ground surface roughness and soil type.
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