基于MeanShift的短波跳频信号快速盲检测

朱政宇; 林宇; 王梓晅; 巩克现; 陈鹏飞; 王忠勇; 梁静

doi:10.11959/j.issn.1000-436x.2022118

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基于MeanShift的短波跳频信号快速盲检测

学术论文 | 更新时间：2024-06-06

- 基于MeanShift的短波跳频信号快速盲检测
- Fast blind detection of short-wave frequency hopping signal based on MeanShift
- 通信学报 2022年43卷第6期页码：200-210
- 作者机构：
  
  1. 郑州大学电气与信息工程学院，河南郑州 450001
  2. 郑州大学电子材料与系统国际联合研究中心，河南郑州 450001
  3. 河南省智能网络和数据分析国际联合实验室，河南郑州 450001
- 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与信号处理、智能反射表面技术、物理层安全技术等" ]
  [ "林宇（1997- ），男，福建莆田人，郑州大学硕士生，主要研究方向为短波信号处理" ]
  [ "王梓晅（1998- ），男，河南周口人，郑州大学博士生，主要研究方向为通信信号处理、多源信息融合等" ]
  [ "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" ]
  [ "陈鹏飞（1998- ），男，河南南阳人，郑州大学硕士生，主要研究方向为深度学习、短波协议识别" ]
  [ "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" ]
  [ "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的研究及应用等" ]
- 基金信息：
  
  国家重点研发计划基金资助项目(2019QY0302);国家重点研发计划基金资助项目(2019YFB1803200);国家自然科学基金资助项目(61922072);国家自然科学基金资助项目(61901417);中国博士后科学基金资助项目(2020M682345);河南省博士后经费资助项目(202001015);河南省高校科技创新人才支持计划资助项目(23HASTIT020)
- DOI：10.11959/j.issn.1000-436x.2022118
  中图分类号： TN92
- 网络出版日期：2022-06，
  
  纸质出版日期：2022-06-25
- 稿件说明：
移动端阅览
朱政宇, 林宇, 王梓晅, 等. 基于MeanShift的短波跳频信号快速盲检测[J]. 通信学报, 2022,43(6):200-210.

Zhengyu ZHU, Yu LIN, Zixuan WANG, et al. Fast blind detection of short-wave frequency hopping signal based on MeanShift[J]. Journal on communications, 2022, 43(6): 200-210.
朱政宇, 林宇, 王梓晅, 等. 基于MeanShift的短波跳频信号快速盲检测[J]. 通信学报, 2022,43(6):200-210. DOI： 10.11959/j.issn.1000-436x.2022118.

Zhengyu ZHU, Yu LIN, Zixuan WANG, et al. Fast blind detection of short-wave frequency hopping signal based on MeanShift[J]. Journal on communications, 2022, 43(6): 200-210. DOI： 10.11959/j.issn.1000-436x.2022118.

摘要

在复杂的短波信道环境下，为了降低各种干扰信号和噪声对跳频信号的影响，实现低信噪比下跳频信号盲检测，结合时频分析技术，提出一种基于 MeanShift 算法的连通域标记跳频信号快速盲检测算法。首先，对信道环境灰度时频图进行二次灰度形态学滤波得到二值化时频图。其次，通过连通域标记算法，计算信号最大持续时长。再次，利用 MeanShift 算法对信号最大持续时长进行聚类分析。最后，结合自适应双门限对聚类结果进行二次判决。仿真结果表明，在无任何先验信息的情况下，所提算法能够在低信噪比下快速分离各种干扰信号与尖锐噪声，实现跳频信号快速盲检测，检测概率较高，在短波信道环境下抗干扰能力较强，计算复杂度较低，具有较高的工程实用价值。

Abstract

In the complex short-wave channel environment

combined with time-frequency analysis technology

a fast blind detection algorithm of the connected domain labeled frequency hopping signals based on MeanShift algorithm was proposed to reduce the influence of various interference signals and noises on frequency hopping signals and realize blind detection of frequency hopping signals under low signal-to-noise ratio.Firstly

the channel environment gray-scale time-frequency map was filtered by the secondary gray-scale morphology to obtain the binary time-frequency map.Secondly

the maximum duration of the signal was calculated by the connected domain labeling algorithm.Then

the MeanShift algorithm was used to cluster the maximum duration of the signal.Finally

the clustering result was made a second judgment by combining with the adaptive double threshold.The simulation results show that the proposed algorithm can quickly separate various interference signals and sharp noise under low signal-to-noise ratio

and realize fast blind detection of frequency hopping signals without any prior information.It has high detection probability

strong anti-interference ability in short-wave channel environment

low computational complexity and high engineering practical value.

关键词

Keywords

references

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