基于熵评价模态分解的雷达信号双谱特征识别

doi:10.12305/j.issn.1001-506X.2021.08.12

Abstract

Abstract:

In order to solve the problems of low accuracy and poor anti-noise of radar signal modulation recognition under low signal to noise ratio (SNR), a recognition method based on entropy evaluation modal decomposition and bispectrum feature extraction is proposed. Based on the characteristics of bispectrum which can suppress Gaussian noise, the feasibility of signal modulation recognition in low SNR is analyzed and the noise term is introduced. Due to the interference of noise term, the noise suppression effect of bispectrum below 0 dB becomes worse. An empirical modal decomposition based on information entropy evaluation is proposed to preprocess the signal and improve the SNR. Finally, a convolutional neural network classifier is designed to recognize different modulation signals. Simulation experiment results show that this method has better anti-noise performance than the traditional method, and can effectively identify different types of signals in low SNR.

Key words: bispectrum, information entropy, convolutional neural network, empirical modal decomposition

CLC Number:

TN971

Xinping MI, Xihong CHEN, Zan LIU, Yongjin LIU, Qiang LIU. Bispectrum feature recognition of radar signal based on entropy evaluation and modal decomposition[J]. Systems Engineering and Electronics, 2021, 43(8): 2116-2123.

Figures/Tables 12

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References 22

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层数	输入尺寸	卷积核	尺寸	步长
卷积层1	227×227×3	96	11/3	4/2
池化层1	27×27×256	256	5/3	1/2
卷积层2	13×13×384	384	3/0	1/1
池化层2	13×13×384	384	3/0	1/1
卷积层3	13×13×384	256	3/3	1/2

类型	SNR/dB
类型	5	0	-5	-10
LFM	16.7	9.3	4.9	2.9
CW	15.2	7.2	4.2	2.5
QPSK	21.6	16.8	9.2	5.3
BPSK	25.6	18.2	10.2	8.1
FSK	18.6	11.0	6.3	4.9
NLFM	16.7	7.4	4.5	3.1

类型	T/s
类型	5	0	-5	-10
LFM	4.8	15.9	54.8	183.8
CW	3.2	13.4	48.2	178.5
QPSK	15.4	28.6	65.2	205.1
BPSK	18.4	32.5	76.2	220.4
FSK	11.8	21.4	56.4	186.3
NLFM	4.1	15.8	61.1	193.9

类型	信号长度
类型	256	512	1 024	2 048
LFM	0.78	0.89	0.91	0.91
CW	0.79	0.90	0.90	0.91
QPSK	0.84	0.91	0.97	0.97
BPSK	0.82	0.93	0.94	0.94
FSK	0.79	0.89	0.93	0.94
NLFM	0.85	0.91	0.94	0.94

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Bispectrum feature recognition of radar signal based on entropy evaluation and modal decomposition

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