SAR ATR Based on Convolutional Neural Network
Tian Zhuangzhuang, Zhan Ronghui, Hu Jiemin, Zhang Jun
ATR Key Laboratory, National University of Defense Technology, Changsha 410073, China
Abstract This study presents a new method of Synthetic Aperture Radar (SAR) image target recognition based on a convolutional neural network. First, we introduce a class separability measure into the cost function to improve this network's ability to distinguish between categories. Then, we extract SAR image features using the improved convolutional neural network and classify these features using a support vector machine. Experimental results using moving and stationary target acquisition and recognition SAR datasets prove the validity of this method.
Key words ： Synthetic Aperture Radar (SAR)
Automatic Target Recognition (ATR)
Convolutional Neural Network (CNN)
Support Vector Machine (SVM)
Back Propagation (BP)
Received: 2016-02-03;
Published: 2016-05-09
Fund: The National Natural Science Foundation of China (61471370)
Cite this article:
. SAR ATR Based on Convolutional Neural Network[J]. JOURNAL OF RADARS, 2016, 5(3): 320-325.
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2016, Vol. 5 
