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Ann-based Sub-surface Monitoring Technique Exploiting Electromagnetic Features Extracted by Gpr Signals : Volume 19, Issue 19 (14/11/2008)

By Caorsi, S.

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Book Id: WPLBN0003998780
Format Type: PDF Article :
File Size: Pages 7
Reproduction Date: 2015

Title: Ann-based Sub-surface Monitoring Technique Exploiting Electromagnetic Features Extracted by Gpr Signals : Volume 19, Issue 19 (14/11/2008)  
Author: Caorsi, S.
Volume: Vol. 19, Issue 19
Language: English
Subject: Science, Advances, Geosciences
Collections: Periodicals: Journal and Magazine Collection (Contemporary), Copernicus GmbH
Historic
Publication Date:
2008
Publisher: Copernicus Gmbh, Göttingen, Germany
Member Page: Copernicus Publications

Citation

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Caorsi, S., & Stasolla, M. (2008). Ann-based Sub-surface Monitoring Technique Exploiting Electromagnetic Features Extracted by Gpr Signals : Volume 19, Issue 19 (14/11/2008). Retrieved from http://www.ebooklibrary.org/


Description
Description: Department of Electronics, University of Pavia, Pavia, Italy. In this work we consider the problem of determining the dielectric characteristics of sub-surface layers by means of GPR systems. In particular, a suitable electromagnetic feature (the RΓ parameter), strictly related to the geophysical parameters of the scenario, is first extracted from the GPR e.m. signal and then fed to an artificial neural network (ANN) in order to derive the dielectric permittivity of the sub-surface layer.

Summary
ANN-based sub-surface monitoring technique exploiting electromagnetic features extracted by GPR signals

Excerpt
Caorsi, S. and Cevini, G.: An electromagnetic approach based on neural networks for the GPR investigation of buried cylinders, IEEE Geosci. Rem. S., 2(1), 3–7, 2005.; Caorsi, S. and Cevini, G.: Electromagnetic reconstruction of layered geometries and multioffset data, in: Proc. of ICEAA 05, Torino, Italy, 405–408, September 2005.; Caorsi, S. and Gamba, P.: Electromagnetic detection of dielectric cylinders by a neural network approach, IEEE Trans. on Geoscience and Remote Sensing, 37(2), 820–827, 1999.; Caorsi, S., Gragnani G. L., and Pastorino, M.: Numerical eletromagnetic inverse scattering solutions for two-dimensional infinite dielectric cylinders buried in a lossy half-space, IEEE Trans. Microwave Theory Tech., 41(2), 352–356, February, 1993.; Carin, L.: Special issue on new advances in subsurface sensing: Systems, modeling, and signal processing, IEEE T. Geosci. Remote, 39(6), 107–1339, June, 2001.; Daniels, D. J., Gunton, D. J., and Scott, H. F.: Introduction to subsurface radar, Proc. IEE, part F, 135, 278–320, August, 1988.; Haykin, S.: Neural Networks, A comprehensive foundation, McMillan, New York, 1994.; Golovko, M. M.: The automatic determination of soil permittivity using the response from a subsurface local object, in Proc. of Ultrawideband and Ultrashort Impulse Signals 2004, 2nd Workshop, Sevastopol, Ukraine, 248–250, September, 2004.; Hoole, S. R. H.: Artificial neural networks in the solution of inverse electromagnetic field problems, IEEE Trans. Magn., 29(2), 1931–1934, March, 1993.; Joachimovicz, N., Pichot, C., and Hugonin, J. P.: Inverse scattering: An iterative numerical method for electromagnetic imaging, IEEE Trans. Antennas Propag., 39(12), 1742–1752, December, 1991.; Kao, C.-P., Li, J., Wang, Y., Xing, H., and Liu, C. R.: Measurement of Layer Thickness and Permittivity Using a New Multilayer Model From GPR Data, IEEE T. Geosci. Remote, 45(8), 2463–2470, August, 2007.; Lambot,S., Slob, E., van den Bosch, C., Stockbroeckx, I., and Vanclooster, M.: Modeling of ground-penetrating radar for accurate characterization of subsurface electric properties, IEEE T. Geosci. Remote, 42, 2555–2568, 2004.; Mellet, J.: Ground penetrating radar applications in engineering, environmental management, and geology, J. Appl. Geophys., 33, 157–166, 1995.; Pierri, R., Soldovieri, F., Liseno, A., and De Blasio, F.: Dielectric Profiles Reconstruction via the Quadratic Approach in 2-D Geometry From Multifrequency and Multifrequency/Multiview Data, IEEE T. Geosci. Remote, 40(12), 2709–2718, 2002.; Pozar, D. M.: Microwave engineering, Addison-Wesley Co. Inc., 1990.; Soldovieri, F., Prisco, G., and Persico, R.: Determination of soil permittivity from GPR data and a microwave tomography approach: a preliminary study, in: Proc. of IWAGPR 2007, Napoli, Italy, , 96–100, June, 2007.; Vellidis, G., Smith, M., Thomas, D., and Asmussen, L.: Detecting wetting front movement in a sandy soil with ground penetrating radar, Trans. ASAE, 33, 1867–1874, 1990.; Youn, H.-S. and Chen,C.-C.: Neural detection for buried pipes using fully-polarimetric ground penetrating radar system, in: Proc of IEEE Antennas and Propagation Society International Symposium 2003, Columbus, Ohio, Vol 2, June, 2003.

 

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