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