dc.contributor.author | Corbett, Brandon | |
dc.contributor.author | Andre, Daniel | |
dc.date.accessioned | 2019-03-11T15:04:07Z | |
dc.date.available | 2019-03-11T15:04:07Z | |
dc.date.issued | 2018-11-15 | |
dc.identifier.citation | Brandon Corbett and Daniel Andre. Using synthetic aperture radar data-dome collections for building feature analysis. Defence and Security Doctoral Symposium, 13-14 November 2018, Swindon, UK | en_UK |
dc.identifier.issn | https://www.cranfield.ac.uk/events/symposia/sym-doc | |
dc.identifier.uri | http://dspace.lib.cranfield.ac.uk/handle/1826/13976 | |
dc.identifier.uri | https://www.cranfield.ac.uk/events/symposia/sym-doc | |
dc.description.abstract | Low-frequency synthetic aperture radar (LF-SAR) is a remote sensing measurement technique that can aid in covert intelligence gathering capabilities for detecting concealed targets in building, and obscured phenomena in general. The Airbus Defence and Space Ltd LF-SAR data dome project has provided a coherently collected three-dimensional data set using airborne circular SAR (CSAR) trajectories, with the potential of providing volumetric SAR imagery of obscured regions inside buildings. Preliminary results of this collection are presented. Both the linear strip-map and CSAR datasets provided contain a great deal of information. Early results show promise, but have revealed the fundamental challenge with low-frequency remote sensing, that being the presence of radio-frequency interference, which reduces the quality of SAR image products. | en_UK |
dc.language.iso | en | en_UK |
dc.publisher | Cranfield University | en_UK |
dc.rights | Attribution 4.0 International | * |
dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | * |
dc.title | Using synthetic aperture radar data-dome collections for building feature analysis | en_UK |
dc.type | Conference paper | en_UK |
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