复杂环境下基于联合特征聚类的多跳频网台分选

朱政宇; 王家政; 梁静; 王忠勇; 巩克现

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

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复杂环境下基于联合特征聚类的多跳频网台分选

学术通信 | 更新时间：2024-06-06

- 复杂环境下基于联合特征聚类的多跳频网台分选
- Multi frequency hopping network station sorting based on joint feature clustering in complex environment
- 通信学报 2023年44卷第9期页码：218-227
- 作者机构：
  
  1. 郑州大学电气与信息工程学院，河南郑州 450001
  2. 东南大学移动通信国家重点实验室，江苏南京 210018
- 作者简介：
  
  [ "朱政宇（1988- ），男，河南周口人，博士，郑州大学副教授，主要研究方向为无线通信信号处理分析与智能处理、电子对抗、短波/超短波通信等" ]
  [ "王家政（2000- ），男，河北邢台人，郑州大学硕士生，主要研究方向为跳频信号检测与分选" ]
  [ "梁静（1981- ），女，河南兰考人，博士，郑州大学教授、博士生导师，主要研究方向为演化计算及应用等" ]
  [ "王忠勇（1965- ），男，江西遂川人，博士，郑州大学教授、博士生导师，主要研究方向为通信信号处理、嵌入式系统等" ]
  [ "巩克现（1976- ），男，山东泰安人，博士，郑州大学教授、博士生导师，主要研究方向为无线通信信号分析与处理、信道编码、无线接入、目标监测及电子对抗等" ]
- 基金信息：
  
  国家重点研发计划基金资助项目(2022YFD2001200);国家自然科学基金资助项目(61922072);河南省自然科学基金资助项目(232300421097);河南省高校科技创新人才支持计划资助项目(23HASTIT019);中国博士后科学基金资助项目(2023T160596);东南大学移动通信国家重点实验室开放课题基金资助项目(2023D11)
- DOI：10.11959/j.issn.1000-436x.2023164
  中图分类号： TN92
- 网络出版日期：2023-09，
  
  纸质出版日期：2023-09-25
- 稿件说明：
移动端阅览
朱政宇, 王家政, 梁静, 等. 复杂环境下基于联合特征聚类的多跳频网台分选[J]. 通信学报, 2023,44(9):218-227.

Zhengyu ZHU, Jiazheng WANG, Jing LIANG, et al. Multi frequency hopping network station sorting based on joint feature clustering in complex environment[J]. Journal on communications, 2023, 44(9): 218-227.
朱政宇, 王家政, 梁静, 等. 复杂环境下基于联合特征聚类的多跳频网台分选[J]. 通信学报, 2023,44(9):218-227. DOI： 10.11959/j.issn.1000-436x.2023164.

Zhengyu ZHU, Jiazheng WANG, Jing LIANG, et al. Multi frequency hopping network station sorting based on joint feature clustering in complex environment[J]. Journal on communications, 2023, 44(9): 218-227. DOI： 10.11959/j.issn.1000-436x.2023164.

摘要

为了从混叠信号中去除干扰并分选出各个跳频网台信号，提出一种基于联合特征聚类的多跳频网台分选算法。首先，对混叠信号进行短时傅里叶变换得到时频矩阵，并根据时频矩阵能量分布直方图进行自适应阈值去噪；其次，通过形态学滤波处理，去除扫频干扰；再次，进行连通域标记，计算各段信号的持续时长和平均能量，以此去除定频干扰和短突发干扰并组成各跳频段的联合特征向量；最后，利用MeanShift算法对各段信号的联合特征向量进行聚类分析，完成各个跳频信号的分选。仿真结果表明，相比传统跳频网台分选算法，所提算法对混叠信号具有更高的分选率、更强的抗干扰能力和更广泛的适用性。

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.

关键词

Keywords

references

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