贺丰收^{1, 2,,},
何友^{1, 3},
刘准钆¹,
徐从安³
1.西北工业大学自动化学院? ?西安? ?710129
2.航空工业雷华电子技术研究所射频综合仿真实验室? ?无锡? ?214063
3.海军航空大学信息融合研究所? ?烟台? ?264001
基金项目:国家自然科学基金(61672431, 61790550, 91538201)

详细信息

作者简介:贺丰收：男，1979年生，高级工程师，博士生，研究方向为雷达数据处理，多源信息融合，深度神经网络等
何友：男，1956年生，中国工程院院士，博士生导师，研究方向为多源信息融合，信号检测，雷达数据处理等
刘准钆：男，1984年生，教授，研究方向为多源信息融合，证据推理，模式识别
徐从安：男，1987年生，博士，讲师，研究方向为多目标跟踪，信息融合等

通讯作者:贺丰收　hefengshou1979@163.com

中图分类号:TN953

计量

文章访问数:4116
HTML全文浏览量:1873
PDF下载量:492
被引次数:0

出版历程

收稿日期:2018-09-18
修回日期:2019-02-18
网络出版日期:2019-03-21
刊出日期:2020-01-21

Research and Development on Applications of Convolutional Neural Networks of Radar Automatic Target Recognition

Fengshou HE^{1, 2,,},
You HE^{1, 3},
Zhunga LIU¹,
Cong’an XU³
1. Institute of Automation, Northwestern Polytechnical University, Xi’an 710129, China
2. Aviation Key Laboratory of Science and Technology on AISSS, AVIC Leihua Electronic Technology Research Institute, Wuxi 214063, China
3. Research Institute of Information Fusion, Naval Aeronautical University, Yantai 264001, China
Funds:The National Natural Science Foundation of China (61672431, 61790550, 91538201)


摘要
摘要:自动目标识别(ATR)是雷达信息处理领域的重要研究方向。由于卷积神经网络(CNN)无需进行特征工程，图像分类性能优越，因此在雷达自动目标识别领域研究中受到越来越多的关注。该文综合论述了CNN在雷达图像处理中的应用进展。首先介绍了雷达自动目标识别相关知识，包括雷达图像的特性，并指出了传统的雷达自动目标识别方法局限性。给出了CNN卷积神经网络原理、组成和在计算机视觉领域的发展历程。然后着重介绍了CNN在雷达自动目标识别中的研究现状，其中详细介绍了合成孔径雷达(SAR)图像目标的检测与识别方法。接下来对雷达自动目标识别面临的挑战进行了深入分析。最后对CNN新理论、新模型，以及雷达新成像技术和未来复杂环境下的应用进行了展望。
关键词:自动目标识别/
目标检测/
合成孔径雷达/
卷积神经网络
Abstract:Automatic Target Recognition(ATR) is an important research area in the field of radar information processing. Because the deep Convolution Neural Network(CNN) does not need to carry out feature engineering and the performance of image classification is superior, it attracts more and more attention in the field of radar automatic target recognition. The application of CNN to radar image processing is reviewed in this paper. Firstly, the related knowledges including the characteristics of the radar image is introduced, and the limitations of traditional radar automatic target recognition methods are pointed out. The principle, composition, development of CNN and the field of computer vision are introduced. Then, the research status of CNN in radar automatic target recognition is provided. The detection and recognition method of SAR image are presented in detail. The challenge of radar automatic target recognition is analyzed. Finally, the new theory and model of convolution neural network, the new imaging technology of radar and the application to complex environments in the future are prospected.
Key words:Automatic Target Recognition (ATR)/
Object detection/
Synthetic Aperture Radar (SAR)/
Convolutional Neural Network (CNN)



PDF全文下载地址:

https://jeit.ac.cn/article/exportPdf?id=7df91f31-a0e4-4f3a-92ef-3c8604dc252a