卷积神经网络在雷达自动目标识别中的研究进展

Translated title of the contribution: Research and Development on Applications of Convolutional Neural Networks of Radar Automatic Target Recognition

Research output: Contribution to journalReview articlepeer-review

41 Scopus citations

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.

Translated title of the contributionResearch and Development on Applications of Convolutional Neural Networks of Radar Automatic Target Recognition
Original languageChinese (Traditional)
Pages (from-to)119-131
Number of pages13
JournalDianzi Yu Xinxi Xuebao/Journal of Electronics and Information Technology
Volume42
Issue number1
DOIs
StatePublished - 1 Jan 2020

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