基于时频能量谱纹理特征的跳频调制方式识别

doi:10.11959/j.issn.1000-436x.2019191

Abstract

Abstract:

For frequency hopping modulation identification,a novel method based on time-frequency energy spectrum texture feature was proposed.Firstly,the time-frequency diagram of the frequency hopping signal was obtained by smoothed pseudo Wigner-Ville distribution,and the background noise of the time-frequency diagram was removed by two-dimensional Wiener filtering to improve the resolution of the time-frequency diagram under low SNR conditions.Then,the connected-domain detection algorithm was used to extract the time-frequency energy spectrum of each hop signal and convert it into a time-frequency gray-scale image.The histogram statistical features and the gray-scale co-occurrence matrix feature were combined to form a 22-dimensional eigenvector.Finally,the feature set was trained,classified and identified by optimized support vector machine classifier.Simulation experiments show that the multi-dimensional feature vector extracted by the algorithm has strong representation ability and avoids the misjudgment caused by the similarity of single features.The average recognition accuracy of the six modulation methods of frequency hopping signals BPSK,QPSK,SDPSK,QASK,64QAM and GMSK is 91.4% under the condition of -4 dB SNR.

Key words: frequency hopping modulation recognition, time-frequency energy spectrum, time-frequency gray scale image, histogram statistics, gray co-occurrence matrix

CLC Number:

TN971

Hongguang LI, Ying GUO, Ping SUI, Zisen QI. Frequency hopping modulation recognition based on time-frequency energy spectrum texture feature[J]. Journal on Communications, 2019, 40(10): 20-29.

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References 22

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输入	输出
输入	BPSK	QPSK	SDPSK	QASK	64QAM	GMSK
BPSK	89.5%	2.3%	8.2%	0	0	0
QPSK	4.5%	91.8%	3.7%	0	0	0
SDPSK	7.5%	2.1%	90.4%	0	0	0
QASK	0	3.1%	0	91.2%	5.7%	0
64QAM	3.9%	0	0	5.4%	90.7%	0
GMSK	1.8%	3.4%	0	0	0	94.8%

Frequency hopping modulation recognition based on time-frequency energy spectrum texture feature

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