LEADER 04930nam 2201021z- 450 001 9910557337403321 005 20231214133419.0 035 $a(CKB)5400000000042504 035 $a(oapen)https://directory.doabooks.org/handle/20.500.12854/76950 035 $a(EXLCZ)995400000000042504 100 $a20202201d2021 |y 0 101 0 $aeng 135 $aurmn|---annan 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aAdvanced Techniques for Ground Penetrating Radar Imaging 210 $aBasel, Switzerland$cMDPI - Multidisciplinary Digital Publishing Institute$d2021 215 $a1 electronic resource (218 p.) 311 $a3-0365-2149-6 311 $a3-0365-2150-X 330 $aGround penetrating radar (GPR) has become one of the key technologies in subsurface sensing and, in general, in non-destructive testing (NDT), since it is able to detect both metallic and nonmetallic targets. GPR for NDT has been successfully introduced in a wide range of sectors, such as mining and geology, glaciology, civil engineering and civil works, archaeology, and security and defense. In recent decades, improvements in georeferencing and positioning systems have enabled the introduction of synthetic aperture radar (SAR) techniques in GPR systems, yielding GPR?SAR systems capable of providing high-resolution microwave images. In parallel, the radiofrequency front-end of GPR systems has been optimized in terms of compactness (e.g., smaller Tx/Rx antennas) and cost. These advances, combined with improvements in autonomous platforms, such as unmanned terrestrial and aerial vehicles, have fostered new fields of application for GPR, where fast and reliable detection capabilities are demanded. In addition, processing techniques have been improved, taking advantage of the research conducted in related fields like inverse scattering and imaging. As a result, novel and robust algorithms have been developed for clutter reduction, automatic target recognition, and efficient processing of large sets of measurements to enable real-time imaging, among others. This Special Issue provides an overview of the state of the art in GPR imaging, focusing on the latest advances from both hardware and software perspectives. 606 $aTechnology: general issues$2bicssc 610 $aGround Penetrating Radar (GPR) 610 $aUnmanned Aerial Vehicles (UAVs) 610 $aSynthetic Aperture Radar (SAR) 610 $aReal Time Kinematic (RTK) 610 $aUltra-Wide-Band (UWB) 610 $alandmine and IED detection 610 $anon-destructive testing 610 $aGPR 610 $acoherence 610 $asemblance 610 $aattribute analysis 610 $aimaging 610 $aGPR trace 610 $ahigh-resolution data 610 $alarge-scale survey 610 $aarchaeological prospection 610 $aGround-Penetrating Radar 610 $avelocity analysis 610 $acoherency functionals 610 $aGPR data processing 610 $aGPR data migration 610 $aspatial-variant convolution neural network (SV-CNN) 610 $aspatial-variant convolution kernel (SV-CK) 610 $aradar image enhancing 610 $aMIMO radar 610 $aneural networks 610 $aimaging radar 610 $aground penetrating radar 610 $awavelet scattering network 610 $amachine learning 610 $asupport vector machine 610 $apipeline identification 610 $asnow 610 $asnow water equivalent (SWE) 610 $astepped-frequency continuous wave radar (SFCW) 610 $asoftware defined radio (SDR) 610 $asnowpack multilayer reflectance 610 $aGround Penetrating Radar 610 $aSynthetic Aperture Radar 610 $alandmine 610 $aImprovised Explosive Device 610 $aradar 610 $anoise attenuation 610 $aGaussian spike impulse noise 610 $adeep convolutional denoising autoencoders (CDAEs) 610 $adeep convolutional denoising autoencoders with network structure optimization (CDAEsNSO) 610 $aapplied geophysics 610 $adigital signal processing 610 $aenhancement of 3D-GPR datasets 610 $aclutter noise removal 610 $aspectral filtering 610 $aground-penetrating radar 610 $anondestructive testing 610 $apipelines detection 610 $amodeling 610 $asignal processing 615 7$aTechnology: general issues 700 $aLo?pez$b Yuri$4edt$01322379 702 $aFerna?ndez$b Mari?a Garci?a$4edt 702 $aLo?pez$b Yuri$4oth 702 $aFerna?ndez$b Mari?a Garci?a$4oth 906 $aBOOK 912 $a9910557337403321 996 $aAdvanced Techniques for Ground Penetrating Radar Imaging$93034934 997 $aUNINA