基于近似熵的Multi-h CPM调制识别算法

doi:10.3969/j.issn.1001-506X.2020.03.026

Abstract

Abstract:

Multi-h continuous phase modulation (CPM) signal is indistinguishable from Single-h CPM signal, when the latter's modulation index is equal to the former's average of modulation indices, for their characteristics are similar. Aiming at this problem, a Multi-h CPM modulation recognition algorithm based on approximate entropy is proposed. The algorithm splits the complete sequence of signal into multiple sub-sequences according to the same modulation index, and discards the extra pattern vectors generated by splicing between symbols, to modify the approximate entropy. Then it uses the difference of entropy between subsequences of the Multi-h CPM signal, the inter-class recognition of Multi-h CPM signal and Single-h CPM signal is completed. Finally, the intra-class identification is accomplished by using probabilistic neural networks. The experimental results show that the algorithm can achieve 90% recognition rate when the signal-to-noise ratio is as low as 11 dB.

Key words: Multi-h continuous phase modulation (CPM), modulation recognition, approximate entropy, probabilistic neural networks

CLC Number:

TN911.3

Kai LIU, Mengwei ZHAO, Qinghua HUANG. Multi-h CPM modulation recognition algorithm based on approximate entropy[J]. Systems Engineering and Electronics, 2020, 42(3): 698-703.

Figures/Tables 12

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References 29

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调制指数	全序列	奇序列	偶序列
[5/16]	[0.09, 0.09]	-	-
[5/16, 6/16]	[0.10, 0.10]	[0.25, 0.25]	[0.27, 0.27]
[11/32]	[0.10, 0.10]	[0.26, 0.26]	[0.26, 0.26]
[6/16]	[0.11, 0.11]	-	-

调制指数	全序列	奇序列	偶序列
[5/16]	[0.09, 0.09]	-	-
[5/16, 6/16]	[0.10, 0.10]	[0.09, 0.09]	[0.11, 0.11]
[11/32]	[0.10, 0.10]	[0.10, 0.10]	[0.10, 0.10]
[6/16]	[0.11, 0.11]	-	-

信号集	Multi-h CPM信号	Single-h CPM信号
A	h=[5/16, 6/16]	h=[11/32]
B	h=[6/16, 7/16]	h=[13/32]
C	h=[7/16, 10/16]	h=[17/32]
D	h=[12/16, 13/16]	h=[25/32]

参数	值
关联长度	L=1
进制数	M=2
脉冲波形	q(t)=LRC
采样率	N_s=8
模式维度	m=2
容错阈值系数	c=0.8

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Multi-h CPM modulation recognition algorithm based on approximate entropy

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