复杂环境下基于联合特征聚类的多跳频网台分选

doi:10.11959/j.issn.1000-436x.2023164

Abstract

Abstract:

In order to remove interference from hybrid signals and sort each frequency hopping station signal, a multi frequency hopping network station sorting algorithm based on joint feature clustering was proposed.Firstly, short-time Fourier transform was applied to the sorted hybrid signals to obtain the time-frequency matrix, and adaptive threshold denoising was carried out according to the energy distribution histogram of time-frequency matrix.Secondly, the sweep interference was removed by morphological filtering.Thirdly, the connected domain was labeled, the duration and average energy of each signal were calculated to remove the fixed frequency interference, and the joint feature vector for each frequency hop was formed.Finally, the MeanShift algorithm was used to cluster and analyze the joint feature vectors of each segment of the signal, completing the sorting of each frequency hopping signal.The simulation results show that the proposed algorithm has higher sorting rate, stronger anti-interference ability and wider applicability to hybrid signals compared with the traditional algorithm.

Key words: frequency hopping signal, network station sorting, MeanShift, time-frequency analysis, connected domain labeling

CLC Number:

TN92

Zhengyu ZHU, Jiazheng WANG, Jing LIANG, Zhongyong WANG, Kexian GONG. Multi frequency hopping network station sorting based on joint feature clustering in complex environment[J]. Journal on Communications, 2023, 44(9): 218-227.

Figures/Tables 16

References 18

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算法	时频分析	预处理	聚类分析	平均聚类时间/s
本文算法	MN	MN	O(n² d₁)	0.812 3
文献[15]算法	—	—	O(n² )	0.787 9
文献[16]算法	MN	MN	O(n² d ₂ )	0.801 7

Multi frequency hopping network station sorting based on joint feature clustering in complex environment

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