电讯技术2018，Vol.58Issue(1)：106-112,7.DOI:10.3969/j.issn.1001-893x.2018.01.019
深度卷积神经网络在SAR自动目标识别领域的应用综述
Applications of Deep Convolutional Neural Network in SAR Automatic Target Recognition:a Summarization
摘要
Abstract
Deep Convolutional Neural Network (DCNN) can automatically learn the target's hierarchical features,and it has wide application prospect in SAR-Automatic Target Recognition (SAR-ATR).Firstly,the basic principle of DCNN is introduced,and the application and development of DCNN in optical image are studied.Then,the basic concept of SAR-ATR is introduced,and the frontier application research and representative network architecture of DCNN in SAR image semantic feature extraction,fragment-level SAR image classification,SAR automatic target recognition based on data enhancement technology,heterogeneous image change detection are reviewed.Finally,the lack of parameter setting and the weak generalization ability of DCNN in SAR-ATR applications are summarized and discussed,and the future research direction is presented.关键词
合成孔径雷达/自动目标识别/深度卷积神经网络/应用综述Key words
synthetic aperture radar(SAR)/automatic target recognition (ATR)/deep convolutional neural network (DCNN)/application summarization分类
信息技术与安全科学引用本文复制引用
许强,李伟,Pierre Loumbi..深度卷积神经网络在SAR自动目标识别领域的应用综述[J].电讯技术,2018,58(1):106-112,7.基金项目
国家自然科学基金资助项目(61302153) （61302153）
航空科学基金资助项目(20160196003) （20160196003）
