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<rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:dc="http://purl.org/dc/elements/1.1/"><rdf:Description rdf:about="https://dk.um.si/IzpisGradiva.php?id=91223"><dc:title>Comparative Study of GPR Acquisition Methods for Shallow Buried Object Detection</dc:title><dc:creator>Smogavec,	Primož	(Avtor)
	</dc:creator><dc:creator>Pongrac,	Blaž	(Avtor)
	</dc:creator><dc:creator>Sarjaš,	Andrej	(Avtor)
	</dc:creator><dc:creator>Kafedziski,	Venceslav	(Avtor)
	</dc:creator><dc:creator>Dončov,	Nabojša	(Avtor)
	</dc:creator><dc:creator>Gleich,	Dušan	(Avtor)
	</dc:creator><dc:subject>GPR</dc:subject><dc:subject>UAV</dc:subject><dc:subject>SFCW radar</dc:subject><dc:subject>acquisition methods</dc:subject><dc:description>This paper investigates the use of ground-penetrating radar (GPR) technology for detecting shallow buried objects, utilizing an air-coupled stepped frequency continuous wave (SFCW) radar system that operates within a 2 GHz bandwidth starting at 500 MHz. Different GPR data acquisition methods for air-coupled systems are compared, specifically down-looking, side-looking, and circular acquisition strategies, employing the back projection algorithm to provide focusing of the acquired GPR data. Experimental results showed that the GPR can penetrate up to 0.6 m below the surface in a down-looking mode. The developed radar and the back projection focusing algorithm were used to acquire data in the side-looking and circular mode, providing focused images with a resolution of 0.1 m and detecting subsurface objects up to 0.3 m below the surface. The proposed approach transforms B-scans of the GPR-based data into 2D images. The provided approach has significant potential for advancing shallow object detection capabilities by transforming hyperbola-based features into point-like features.</dc:description><dc:publisher>MDPI</dc:publisher><dc:date>2024</dc:date><dc:date>2024-11-29 13:02:03</dc:date><dc:type>Članek v reviji</dc:type><dc:identifier>91223</dc:identifier><dc:language>sl</dc:language><dc:rights>© 2024 by the authors.</dc:rights></rdf:Description></rdf:RDF>
