Radar signal recognition method based on deep convolutional neural network and bispectrum feature

被引：4

作者：

Liu Y. ^{[1
]}

Tian R. ^{[1
]}

Wang X. ^{[1
]}

机构：

[1] School of Aviation Operations and Services, Aviation University of Air Force, Changchun

来源：

Xi Tong Gong Cheng Yu Dian Zi Ji Shu/Systems Engineering and Electronics | 2019年 / 41卷 / 09期

关键词：

Bispectrum; Deep convolutional neural network; Feature extraction; Radar signal recognition;

D O I：

10.3969/j.issn.1001-506X.2019.09.12

中图分类号：

学科分类号：

摘要：

Aiming at the problem of strong subjectivity and feature redundancy of radar signal recognition in the complex electromagnetic environment, a recognition method based on deep convolutional neural network is proposed. By extracting the bispectrum information of the radar signal as the input of the network model, the network model is used to automatically learn the deep features, identify the different modulation pattern signals, and compare the recognition results of the deep network models with different structures. The results of simulation experiment show that compared with the traditional radar signal recognition method, the proposed method has improved recognition rate and noise immunity. © 2019, Editorial Office of Systems Engineering and Electronics. All right reserved.

引用

页码：1998 / 2005

页数：7

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