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)

[thumbnail of Izzo-etal-IEEETAES2017-Multi-model-CFAR-detection-in-FOPEN-SAR-images]
Preview
Text. Filename: Izzo_etal_IEEETAES2017_Multi_model_CFAR_detection_in_FOPEN_SAR_images.pdf
Final Published Version
License: Creative Commons Attribution 3.0 logo

Download (1MB)| Preview

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.