Target recognition using the transfer learning-based deep convolutional neural networks for SAR images

LI Song; WEI Zhonghao; ZHANG Bingchen; HONG Wen

doi:10.7523/j.issn.2095-6134.2018.01.010

Journal of University of Chinese Academy of Sciences >

2018 , Vol. 35 >Issue 1: 75 - 83

DOI: https://doi.org/10.7523/j.issn.2095-6134.2018.01.010

Target recognition using the transfer learning-based deep convolutional neural networks for SAR images

LI Song ,
WEI Zhonghao ,
ZHANG Bingchen ,
HONG Wen

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1. Institute of Electronics, Chinese Academy of Sciences, Beijing 100190, China;
2. National Key Laboratory of Microwave Imaging Technology, Beijing 100190, China;
3. University of Chinese Academy of Sciences, Beijing 100049, China

Received date: 2017-02-10

Revised date: 2017-03-28

Online published: 2018-01-15

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Abstract

The automatic target recognition procedure of synthetic aperture radar (SAR) generally includes two steps, feature extraction and classifier training. Based on the development of deep convolutional neural networks, we present a new method of SAR target recognition. This method automatically learns the hierarchies of features from different targets, which means it avoids the non-normalization caused by manual feature extraction. Then the transfer learning technology is applied to avert the occurrence of locally optimal solution and accelerate the training procedure. Finally we use the moving and stationary target acquisition and recognition database to verify our method.

Key words： synthetic aperture radar(SAR); automatic target recognition(ATR); deep convolu-tional neural networks(DNNs); transfer learning

Cite this article

LI Song , WEI Zhonghao , ZHANG Bingchen , HONG Wen . Target recognition using the transfer learning-based deep convolutional neural networks for SAR images[J]. Journal of University of Chinese Academy of Sciences, 2018 , 35(1) : 75 -83 . DOI: 10.7523/j.issn.2095-6134.2018.01.010

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