基于卷积神经网络的SAR图像目标识别研究

田壮壮 占荣辉 胡杰民 张军

田壮壮, 占荣辉, 胡杰民, 张军. 基于卷积神经网络的SAR图像目标识别研究[J]. 雷达学报, 2016, 5(3): 320-325. doi: 10.12000/JR16037
引用本文: 田壮壮, 占荣辉, 胡杰民, 张军. 基于卷积神经网络的SAR图像目标识别研究[J]. 雷达学报, 2016, 5(3): 320-325. doi: 10.12000/JR16037
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

基于卷积神经网络的SAR图像目标识别研究

doi: 10.12000/JR16037
基金项目: 

国家自然科学基金(61471370)

详细信息
    作者简介:

    田壮壮(1993-),男,硕士生,研究方向为雷达目标识别。E-mail:tzz14@nudt.edu.cn;占荣辉(1978-),男,讲师,博士,研究方向为雷达目标识别、雷达信息处理;胡杰民(1983-),男,讲师,博士,研究方向为空间目标识别、雷达成像;张军(1973-),男,研究员,博士,研究方向为雷达智能信号处理、制导雷达应用技术。

    通讯作者:

    田壮壮tzz14@nudt.edu.cn

SAR ATR Based on Convolutional Neural Network

Funds: 

The National Natural Science Foundation of China (61471370)

  • 摘要: 针对合成孔径雷达(Synthetic Aperture Radar, SAR)的图像目标识别应用, 该文提出了一种基于卷积神经网络(Convolutional Neural Network, CNN)的SAR图像目标识别方法。首先通过在误差代价函数中引入类别可分性度量, 提高了卷积神经网络的类别区分能力;然后利用改进后的卷积神经网络对SAR图像进行特征提取;最后利用支持向量机(Support Vector Machine, SVM)对特征进行分类。使用美国运动和静止目标获取与识别(Moving and Stationary Target Acquisition and Recognition, MSTAR)SAR图像数据进行实验, 识别结果证明了所提方法的有效性。

     

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出版历程
  • 收稿日期:  2016-02-03
  • 修回日期:  2016-03-15
  • 网络出版日期:  2016-06-28

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