Multi-model CFAR detection in FOliage PENetrating SAR images

Alessio Izzo; Marco Liguori; Carmine Clemente; Carmelo Galdi; Maurizio Di Bisceglie; John J. Soraghan

doi:10.1109/TAES.2017.2672018

Multi-model CFAR detection in FOliage PENetrating SAR images

Alessio Izzo, Marco Liguori, Carmine Clemente, Carmelo Galdi, Maurizio Di Bisceglie, John J. Soraghan

Electronic And Electrical Engineering

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11 Citations (Scopus)

156 Downloads (Pure)

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.

Original language	English
Pages (from-to)	1769-1780
Number of pages	12
Journal	IEEE Transactions on Aerospace and Electronic Systems
Volume	53
Issue number	4
Early online date	14 Mar 2017
DOIs	https://doi.org/10.1109/TAES.2017.2672018
Publication status	Published - 31 Aug 2017

Keywords

constant false alarm ratio
foliage penetrating
extreme value distributions
location scale
forest densities
vehicles detection
false alarm probabilities

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10.1109/TAES.2017.2672018Licence: CC BY 3.0

Izzo-etal-IEEETAES2017-Multi-model-CFAR-detection-in-FOPEN-SAR-imagesFinal published version, 1.02 MBLicence: CC BY 3.0

Cite this

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title = "Multi-model CFAR detection in FOliage PENetrating SAR images",

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.",

keywords = "constant false alarm ratio, foliage penetrating, extreme value distributions, location scale, forest densities, vehicles detection, false alarm probabilities",

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AU - Clemente, Carmine

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AU - Di Bisceglie, Maurizio

AU - Soraghan, John J.

PY - 2017/8/31

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KW - constant false alarm ratio

KW - foliage penetrating

KW - extreme value distributions

KW - location scale

KW - forest densities

KW - vehicles detection

KW - false alarm probabilities

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JF - IEEE Transactions on Aerospace and Electronic Systems

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ER -

Multi-model CFAR detection in FOliage PENetrating SAR images

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Keywords

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Signal Processing Solutions for the Networked Battlespace

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Multi-model CFAR detection in FOliage PENetrating SAR images

Abstract

Keywords

Access to Document

Other files and links

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Signal Processing Solutions for the Networked Battlespace

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