基于AlexNet模型的雷达信号调制类型识别

doi:10.13229/j.cnki.jdxbgxb20171056

Abstract

Abstract:

Aiming at the complex electromagnetic environment in modern battlefield, the accuracy of traditional radar modulation signal recognition method based on conventional five?parameter feature is low under low signal?to?noise ratio (-6 dB). In this paper, AlexNet convolution neural network model in deep learning is used to automatically extract various feature details of image, which can replace the huge Feature Engineering designed by hand to realize signal recognition under low signal?to?noise ratio. Firstly, the time?frequency image of radar modulation signal is generated by smoothing pseudo?Wigner?Ville time?frequency analysis in time?frequency domain; then, the time?frequency image is preprocessed by median and mean filtering combined with denoising; finally, the AlexNet model is trained by using image processor GPU under the deep learning framework Tensor flow, and CW, LFM, E are trained. Seven kinds of radar signals, QFM, DLFM, BFSK, BPSK and QPSK, are automatically extracted and selected to realize automatic recognition of radar signals. The simulation results show that the overall recognition rate of the other six radar signals, except QPSK signal, is more than 90% at the signal?to?noise ratio -6 dB, which is better than that of the non?deep learning and LeNet5 convolution neural network, thus verifying the validity of the method for radar signal recognition at low signal?to?noise ratio.

Key words: signal and information processing, smooth pseudo Wigner?Ville, midial filter, mean filter, deep learning

CLC Number:

TN971.1

Li⁃min GUO,Xin CHEN,Tao CHEN. Radar signal modulation type recognition based on AlexNet model[J].Journal of Jilin University(Engineering and Technology Edition), 2019, 49(3): 1000-1008.

Figures/Tables 9

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层数	输入尺寸	卷积核	卷池尺寸	卷池步长	输出特征
1	227×227×3	96	11/3	4/2	27×27×96
2	27×27×256	256	5/3	1/2	13×13×256
3	13×13×384	384	3/0	1/1	13×13×384
4	13×13×384	384	3/0	1/1	13×13*×84
5	13×13×385	256	3/3	1/2	6×6×256

信号类型	载频/MHz	采样频率/MHz	采样点N	调频斜率K
CW	0~30	200	512	-
LFM	10~50	200	512	2~3B/T
EQFM	10~40	200	512	-
DLFM	10~30	200	512	2~3B/T
BFSK	fc1=(10~30) fc2=(10~40)	200	512	-
BPSK	20~30	200	512	-
QPSK	20~30	200	512	-

平台	信噪比 (dB) /时间(s)
平台	-10	-8	-6	-4	-2	0
GPU	1730	1680	1645	1654	1623	1400
CPU	14900	4680	14780	14650	14300	14300

Radar signal modulation type recognition based on AlexNet model

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