Multi-model CFAR detection in FOliage PENetrating SAR images
Izzo, Alessio and Liguori, Marco and Clemente, Carmine and Galdi, Carmelo and Di Bisceglie, Maurizio and Soraghan, John J. (2017) Multi-model CFAR detection in FOliage PENetrating SAR images. IEEE Transactions on Aerospace and Electronic Systems, 53 (4). pp. 1769-1780. ISSN 0018-9251 (https://doi.org/10.1109/TAES.2017.2672018)
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Abstract
A multi-model approach for Constant False Alarm Ratio (CFAR) detection of vehicles through foliage in FOliage PENetrating (FOPEN) SAR images is presented. Extreme value distributions and Location Scale properties are exploited to derive an adaptive CFAR approach that is able to cope with different forest densities. Performance analysis on real data is carried out to estimate the detection and false alarm probabilities in the presence of a ground truth.
ORCID iDs
Izzo, Alessio ORCID: https://orcid.org/0000-0001-6009-8757, Liguori, Marco, Clemente, Carmine ORCID: https://orcid.org/0000-0002-6665-693X, Galdi, Carmelo, Di Bisceglie, Maurizio and Soraghan, John J. ORCID: https://orcid.org/0000-0003-4418-7391;-
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Item type: Article ID code: 59551 Dates: DateEvent31 August 2017Published14 March 2017Published Online17 January 2017AcceptedSubjects: Technology > Electrical engineering. Electronics Nuclear engineering
Technology > Motor vehicles. Aeronautics. AstronauticsDepartment: Faculty of Engineering > Electronic and Electrical Engineering
Technology and Innovation Centre > Sensors and Asset ManagementDepositing user: Pure Administrator Date deposited: 23 Jan 2017 16:21 Last modified: 11 Nov 2024 11:23 Related URLs: URI: https://strathprints.strath.ac.uk/id/eprint/59551