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Autore: | López Yuri |
Titolo: | Advanced Techniques for Ground Penetrating Radar Imaging |
Pubblicazione: | Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 |
Descrizione fisica: | 1 electronic resource (218 p.) |
Soggetto topico: | Technology: general issues |
Soggetto non controllato: | Ground Penetrating Radar (GPR) |
Unmanned Aerial Vehicles (UAVs) | |
Synthetic Aperture Radar (SAR) | |
Real Time Kinematic (RTK) | |
Ultra-Wide-Band (UWB) | |
landmine and IED detection | |
non-destructive testing | |
GPR | |
coherence | |
semblance | |
attribute analysis | |
imaging | |
GPR trace | |
high-resolution data | |
large-scale survey | |
archaeological prospection | |
Ground-Penetrating Radar | |
velocity analysis | |
coherency functionals | |
GPR data processing | |
GPR data migration | |
spatial-variant convolution neural network (SV-CNN) | |
spatial-variant convolution kernel (SV-CK) | |
radar image enhancing | |
MIMO radar | |
neural networks | |
imaging radar | |
ground penetrating radar | |
wavelet scattering network | |
machine learning | |
support vector machine | |
pipeline identification | |
snow | |
snow water equivalent (SWE) | |
stepped-frequency continuous wave radar (SFCW) | |
software defined radio (SDR) | |
snowpack multilayer reflectance | |
Ground Penetrating Radar | |
Synthetic Aperture Radar | |
landmine | |
Improvised Explosive Device | |
radar | |
noise attenuation | |
Gaussian spike impulse noise | |
deep convolutional denoising autoencoders (CDAEs) | |
deep convolutional denoising autoencoders with network structure optimization (CDAEsNSO) | |
applied geophysics | |
digital signal processing | |
enhancement of 3D-GPR datasets | |
clutter noise removal | |
spectral filtering | |
ground-penetrating radar | |
nondestructive testing | |
pipelines detection | |
modeling | |
signal processing | |
Persona (resp. second.): | FernándezMaría García |
LópezYuri | |
Sommario/riassunto: | Ground 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. |
Titolo autorizzato: | Advanced Techniques for Ground Penetrating Radar Imaging |
Formato: | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione: | Inglese |
Record Nr.: | 9910557337403321 |
Lo trovi qui: | Univ. Federico II |
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