基于SE-ResNeXt网络的低信噪比LPI雷达辐射源信号识别

doi:10.12305/j.issn.1001-506X.2022.12.11

Abstract

Abstract:

Aiming at the problem of low signal to noise ratio (SNR) and low probability of intercept (LPI) radar pulse waveform recognition accuracy, a radar emitter signal recognition method based on time-frequency analysis, squeeze-excitation (SE) and ResNeXt network is proposed. Firstly, the radar time domain signal is transformed into a two-dimensional time-frequency image (TFI) by Choi-Williams distribution (CWD); then, the TFI pre-processing is used to reduce the noise interference and the difference in frequency dimension location distribution, adapting to deep learning network input; finally, the TFI features are extracted by adding dilated convolution and SE structure on the basis of ResNeXt to achieve radar emitter classification. The experimental results show that when the SNR is as low as -8 dB, the overall recognition accuracy of the method for 12 types of common LPI radar waveforms can still reach 98.08%.

Key words: low probability of intercept (LPI) radar waveform, emitter signal recognition, residual network, squeeze excitation (SE) structure, time-frequency analysis

CLC Number:

TN957.5

Guiguang XU, Xudong WANG, Fei WANG, Guobing HU, Yongxing GAO, Zehu LUO. LPI radar emitter signals recognition in low SNR based on SE-ResNeXt network[J]. Systems Engineering and Electronics, 2022, 44(12): 3676-3684.

Figures/Tables 17

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Table 1

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References 30

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层名	输出尺寸	网络结构(16×4 d)
第1层	112×112	卷积, 7×7, 64, 步长2
第2层	56×56	最大值池化3×3, 步长2
第2层	56×56	$ \left[\begin{array}{l}\text { 卷积, } 1 \times 1, 64, 1 \\\text { 卷积, } 3 \times 3, 64, 16 \\\text { 卷积, } 1 \times 1, 128, 1 \\\mathrm{FC}, [8, 128]\end{array}\right]$
第3层	28×28	$\left[\begin{array}{l}\text { 卷积, } 1 \times 1, 128, 1 \\\text { 卷积, } 3 \times 3, 128, 16 \\\text { 卷积, } 1 \times 1, 256, 1 \\\mathrm{FC}, [16, 256]\end{array}\right] $
第4层	28×28	$ \left[\begin{array}{l}\text { 卷积, } 1 \times 1, 256, 1 \\\text { 卷积, } 3 \times 3, 256, 16 \\\text { 卷积, } 1 \times 1, 512, 1 \\\mathrm{FC}, [32, 512]\end{array}\right]$
第5层	28×28	$ \left[\begin{array}{l}\text { 卷积, } 1 \times 1, 512, 1 \\\text { 卷积, } 3 \times 3, 512, 16 \\\text { 卷积, } 1 \times 1, 1024, 1 \\\mathrm{FC}, [64, 1024]\end{array}\right]$
-	1×1	GAP, 12-d FC, Softmax

信号类型	参数	取值范围
LFM	载频f_c	U(1/10, 1/3)
LFM	带宽B	U(1/10, 1/5)
Costas	跳频序列L	{3, 4, 5, 6}
Costas	基准频率f_min	U(1/24, 1/20)
BPSK	载频f_c	U(1/10, 1/3)
BPSK	巴克码长度L_c	{7, 11, 13}
Frank P1, P2	载频f_c	U(1/10, 1/3)
	相位控制数M	^{[8, 12]} P2码M为偶数
	相位子波数cpp	^{[2, 5]}
P3, P4	载频f_c	U(1/10, 1/3)
	相位控制数M	{36, 64, 81, 100}
	相位子波数cpp	^{[2, 5]}
T1, T2	载频f_c	U(1/10, 1/3)
T1, T2	波形段数k	^{[4, 6]}
T3, T4	载频f_c	U(1/10, 1/3)
	波形段数k	^{[4, 6]}
	调制带宽B	U(1/20, 1/8)

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LPI radar emitter signals recognition in low SNR based on SE-ResNeXt network

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