DocumentCode :
406169
Title :
Automatic target recognition of ISAR object images based on neural network
Author :
Ning, Wu ; Chen, Wugun ; Zhang, Xinggan
Author_Institution :
Dept. of Electron. Eng., Nanjing Univ. of Aeronaut. & Astronaut., China
Volume :
1
fYear :
2003
fDate :
14-17 Dec. 2003
Firstpage :
373
Abstract :
In this paper an integrate approach of automatic target recognition is proposed with a three-feedforward neural network. It includes images pre-processing, feature extraction and automatic target recognition and classification of ISAR object images. Using the log-spiral transform after moving the centroid of ISAR images to the original point makes the target recognition invariant on translation, rotation and scale. The approach improves the ratio of accurate recognition and reduces the amount of calculation. The results of experiments with field data show that the approach is effective.
Keywords :
feature extraction; feedforward neural nets; image classification; military computing; military radar; radar computing; radar imaging; radar target recognition; synthetic aperture radar; ISAR object images; automatic target recognition; feature extraction; feedforward neural network; images preprocessing; log-spiral transform; neural network; Character recognition; Feature extraction; Image recognition; Neural networks; Optical scattering; Pixel; Radar imaging; Radar scattering; Reconnaissance; Target recognition;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks and Signal Processing, 2003. Proceedings of the 2003 International Conference on
Conference_Location :
Nanjing
Print_ISBN :
0-7803-7702-8
Type :
conf
DOI :
10.1109/ICNNSP.2003.1279287
Filename :
1279287
Link To Document :
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