"The identification of buried cables, pipes, conduits, and other cylindrical utilities is a very important task in civil engineering. In the last years, several methods have been proposed in the literature for tackling this problem Most commonly employed approaches are based on the use of Ground Penetrating Radars, i.e., they extract the needed information about the unknown scenario starting from the electromagnetic field collected by a set of antennas. In the present paper, a statistical method, based on the use of smart antenna techniques, is used for the localization of a single buried object In particular, two efficient algorithms for the estimation of the directions of arrival of the electromagnetic waves scattered by the targets, namely the MUltiple SIgnal Classification and the Support Vector Regression, are considered and their performances are compared. (c) 2013 Elsevier B.V. All rights reserved."
Meschino, S., Pajewski, L., Pastorino, M., Randazzo, A., Schettini, G. (2013). Detection of subsurface metallic utilities by means of a SAP technique: Comparing MUSIC- and SVM-based approaches. JOURNAL OF APPLIED GEOPHYSICS, 97(10), 60-68 [10.1016/j.jappgeo.2013.01.011].
Detection of subsurface metallic utilities by means of a SAP technique: Comparing MUSIC- and SVM-based approaches
MESCHINO, SIMONE;PAJEWSKI, LARA;SCHETTINI, Giuseppe
2013-01-01
Abstract
"The identification of buried cables, pipes, conduits, and other cylindrical utilities is a very important task in civil engineering. In the last years, several methods have been proposed in the literature for tackling this problem Most commonly employed approaches are based on the use of Ground Penetrating Radars, i.e., they extract the needed information about the unknown scenario starting from the electromagnetic field collected by a set of antennas. In the present paper, a statistical method, based on the use of smart antenna techniques, is used for the localization of a single buried object In particular, two efficient algorithms for the estimation of the directions of arrival of the electromagnetic waves scattered by the targets, namely the MUltiple SIgnal Classification and the Support Vector Regression, are considered and their performances are compared. (c) 2013 Elsevier B.V. All rights reserved."I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
