Title :
Electromagnetic infrastructure monitoring: The exploitation of GPR data and neural networks for multi-layered geometries
Author :
Caorsi, Salvatore ; Stasolla, Mattia
Author_Institution :
Dept. of Electron., Univ. of Pavia, Pavia, Italy
Abstract :
In this paper, an inversion ANN-based algorithm for the estimation of geophysical properties (i.e. thickness and permittivity) of subsurface layers in stratified geometries is presented. The basic procedure for the analysis of GPR scans of single subsurface layers placed over a uniform background recently proposed by the authors has been here extended and inserted into a general framework where each stratum is recursively processed.
Keywords :
geophysical techniques; ground penetrating radar; neural nets; artificial neural networks; electromagnetic infrastructure monitoring; geophysical properties; ground penetrating radar; multilayered geometries; single subsurface layers; Artificial neural networks; Atmospheric modeling; Feature extraction; Geometry; Ground penetrating radar; Monitoring; Permittivity; GPR; artificial neural networks; infrastructure monitoring;
Conference_Titel :
Geoscience and Remote Sensing Symposium (IGARSS), 2010 IEEE International
Conference_Location :
Honolulu, HI
Print_ISBN :
978-1-4244-9565-8
Electronic_ISBN :
2153-6996
DOI :
10.1109/IGARSS.2010.5650871