DocumentCode :
2201855
Title :
A novel technique for feature-based aircraft identification from high resolution airborne ISAR images
Author :
Ricardi, Niccolò ; Aprile, Angelo ; Acqua, Fabio Dell
Author_Institution :
Dept. of Electron., Univ. of Pavia, Pavia, Italy
fYear :
2012
fDate :
22-27 July 2012
Firstpage :
2082
Lastpage :
2085
Abstract :
In this paper we propose a new method for aircraft identification and classification using high-resolution ISAR images acquired from an airborne radar sensor. The proposed method takes advantage of some of the geometric features extracted from the image, and some signal features as well (like the Jet Engine Modulation phenomenon that allows us detecting and analyzing the engines of the unknown aircraft). In the next session we will provide a brief explanation of the problem, in order to show the proposed method. An ad hoc classification database has been developed, containing physical characteristics of some aircrafts. Features extracted from radar data have been compared with the database content for classification and some preliminary results have already been obtained. These results appear encouraging and will be shown in the paper.
Keywords :
airborne radar; aircraft; feature extraction; geometry; image classification; image resolution; jet engines; radar imaging; radar resolution; synthetic aperture radar; ad hoc classification database; airborne radar sensor; aircraft classification; feature-based aircraft identification; geometric feature extraction; high resolution airborne ISAR image; jet engine modulation phenomenon; signal feature; Airborne radar; Aircraft; Feature extraction; Military aircraft; Radar cross section; Radar imaging; Inverse synthetic aperture radar; Target classification; airborne radar; aircrafts;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Geoscience and Remote Sensing Symposium (IGARSS), 2012 IEEE International
Conference_Location :
Munich
ISSN :
2153-6996
Print_ISBN :
978-1-4673-1160-1
Electronic_ISBN :
2153-6996
Type :
conf
DOI :
10.1109/IGARSS.2012.6350962
Filename :
6350962
Link To Document :
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