Volume 5 Issue 3
Jun.  2016
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Article Navigation >  Journal of Radars  > 2016  >  5(3): 320-325
Tian Zhuangzhuang, Zhan Ronghui, Hu Jiemin, Zhang Jun. SAR ATR Based on Convolutional Neural Network[J]. Journal of Radars, 2016, 5(3): 320-325. doi: 10.12000/JR16037
Citation: Tian Zhuangzhuang, Zhan Ronghui, Hu Jiemin, Zhang Jun. SAR ATR Based on Convolutional Neural Network[J]. Journal of Radars, 2016, 5(3): 320-325. doi: 10.12000/JR16037
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SAR ATR Based on Convolutional Neural Network

doi: 10.12000/JR16037

  • ATR Key Laboratory, National University of Defense Technology, Changsha 410073, China

Funds:

The National Natural Science Foundation of China (61471370)

  • Received Date: 2016-02-03
  • Rev Recd Date: 2016-03-15
  • Publish Date: 2016-06-28
    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.

     

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