Discrimination of buried objects using time-frequency analysis and waveform norms

Morrow, Ivor L.; Wirth, Sebastian G.; Finnis, Mark V.

dc.contributor.author	Morrow, Ivor L.
dc.contributor.author	Wirth, Sebastian G.
dc.contributor.author	Finnis, Mark V.
dc.date.accessioned	2019-04-15T11:32:19Z
dc.date.available	2019-04-15T11:32:19Z
dc.date.issued	2017-01-09
dc.identifier.citation	Morrow I, Wirth S & Finnis M (2017) Discrimination of buried objects using time-frequency analysis and waveform norms. In: 2016 Loughborough Antennas & Propagation Conference (LAPC), Loughborough, 14-15 November 2016.	en_UK
dc.identifier.isbn	978-1-5090-0784-4
dc.identifier.uri	https://doi.org/10.1109/LAPC.2016.7807605
dc.identifier.uri	http://dspace.lib.cranfield.ac.uk/handle/1826/14082
dc.description.abstract	Ground Penetrating Radar (GPR) are widely used to probe the sub-surface. Recently, various time-frequency analyses has been proposed to discriminate buried land mines from other clutter objects and thus reduce GPR false alarm rates. This paper examines the possibility for discrimination and assesses it experimentally. The approach uses the Choi-Williams time-frequency transform to analyse ultra-wideband signal returns from a range of shallow buried objects. Single Value Decomposition is performed on isolated object time-frequency signatures. The signatures are evaluated using a set of waveform norms that discriminate in time, frequency and energy content. The results indicate that this approach could improve land mine detection rates and reduce false alarms.	en_UK
dc.language.iso	en	en_UK
dc.publisher	IEEE	en_UK
dc.rights	Attribution-NonCommercial 4.0 International	*
dc.rights.uri	http://creativecommons.org/licenses/by-nc/4.0/	*
dc.subject	remote sensing	en_UK
dc.subject	time-frequency transforms	en_UK
dc.subject	signal theory and analysis	en_UK
dc.title	Discrimination of buried objects using time-frequency analysis and waveform norms	en_UK
dc.type	Conference paper	en_UK