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Automatic Target Recognition by Means of Polarimetric ISAR Images and Neural Networks

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5 Author(s)
M. Martorella ; Dept. of "Ingegneria dell'Informazione", University of Pisa, via Caruso 16, 56122 Pisa, Italy ; E. Giusti ; A. Capria ; F. Berizzi
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Inverse Synthetic Aperture Radar (ISAR) images are often used for classifying and recognising targets. Moreover the use of a fully polarimentric ISAR image enhances classiication capabilities. In this paper, the authors propose a novel ATR technique based on the use of fully polarimetric ISAR images and Neural Networks. In order to reduce the amount of data processed by the classifier, the brightest scattering centres are first extracted by means of the Pol-CLEAN technique and then their scattering matrices are decomposed using Cameron's decomposition. The proposed ATR algorithm is finally tested on real data.

Published in:

IGARSS 2008 - 2008 IEEE International Geoscience and Remote Sensing Symposium  (Volume:4 )

Date of Conference:

7-11 July 2008