Adaptive Detection of Low-Signature Targets in Forward-Looking GPR Imagery
We present an image-domain adaptive likelihood ratio tests (LRT) detector for low-signature target detection in forward-looking ground-penetrating radar. We exploit multiview tomographic images of the scene under investigation to iteratively adapt the statistics of the targets and clutter arising fr...
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| Veröffentlicht in: | IEEE geoscience and remote sensing letters 2018-10, Vol.15 (10), p.1520-1524 |
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| container_title | IEEE geoscience and remote sensing letters |
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| creator | Comite, D. Ahmad, F. Dogaru, T. Amin, M. G. |
| description | We present an image-domain adaptive likelihood ratio tests (LRT) detector for low-signature target detection in forward-looking ground-penetrating radar. We exploit multiview tomographic images of the scene under investigation to iteratively adapt the statistics of the targets and clutter arising from the interface roughness. Using numerical electromagnetic data, it is shown that the proposed adaptive LRT detector provides significantly lower false-alarm rates compared with its nonadaptive counterpart while providing comparable detection performance. |
| doi_str_mv | 10.1109/LGRS.2018.2852684 |
| format | Article |
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G.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c293t-9bcede944351fc8247cec7b01a3d10b6a1074363aa885ecab63dedd3033a430a3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2018</creationdate><topic>Adaptive detection</topic><topic>Clutter</topic><topic>Detection</topic><topic>Detectors</topic><topic>False alarms</topic><topic>forward-looking GPR (FL-GPR)</topic><topic>Ground penetrating radar</topic><topic>Image detection</topic><topic>Imagery</topic><topic>Interface roughness</topic><topic>Land mines</topic><topic>Light rail systems</topic><topic>Likelihood ratio</topic><topic>Medical imaging</topic><topic>microwave imaging</topic><topic>microwave tomography</topic><topic>Position measurement</topic><topic>Radar</topic><topic>Radar detection</topic><topic>Radar imaging</topic><topic>Radar signatures</topic><topic>Rough surfaces</topic><topic>Roughness</topic><topic>Statistical methods</topic><topic>Surface roughness</topic><topic>Target detection</topic><topic>Target recognition</topic><topic>terrain clutter</topic><topic>Tomography</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Comite, D.</creatorcontrib><creatorcontrib>Ahmad, F.</creatorcontrib><creatorcontrib>Dogaru, T.</creatorcontrib><creatorcontrib>Amin, M. 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G.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Adaptive Detection of Low-Signature Targets in Forward-Looking GPR Imagery</atitle><jtitle>IEEE geoscience and remote sensing letters</jtitle><stitle>LGRS</stitle><date>2018-10-01</date><risdate>2018</risdate><volume>15</volume><issue>10</issue><spage>1520</spage><epage>1524</epage><pages>1520-1524</pages><issn>1545-598X</issn><eissn>1558-0571</eissn><coden>IGRSBY</coden><abstract>We present an image-domain adaptive likelihood ratio tests (LRT) detector for low-signature target detection in forward-looking ground-penetrating radar. We exploit multiview tomographic images of the scene under investigation to iteratively adapt the statistics of the targets and clutter arising from the interface roughness. 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| subjects | Adaptive detection Clutter Detection Detectors False alarms forward-looking GPR (FL-GPR) Ground penetrating radar Image detection Imagery Interface roughness Land mines Light rail systems Likelihood ratio Medical imaging microwave imaging microwave tomography Position measurement Radar Radar detection Radar imaging Radar signatures Rough surfaces Roughness Statistical methods Surface roughness Target detection Target recognition terrain clutter Tomography |
| title | Adaptive Detection of Low-Signature Targets in Forward-Looking GPR Imagery |
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