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一种改进YOLOv8的跳频网台分选算法

朱政宇 赵航冉 王梓晅 王忠勇 巩克现 梁静

电子学报2025,Vol.53Issue(2):385-394,10.
电子学报2025,Vol.53Issue(2):385-394,10.DOI:10.12263/DZXB.20240487

一种改进YOLOv8的跳频网台分选算法

A Frequency Hopping Network Station Sorting Algorithm Based on Improved YOLOv8

朱政宇 1赵航冉 2王梓晅 2王忠勇 2巩克现 2梁静2

作者信息

  • 1. 郑州电气与信息工程学院,河南 郑州 450001||东南大学移动通信国家重点实验室,江苏 南京 210018||河南省智能网络和数据分析国际联合实验室,河南 郑州 450001
  • 2. 郑州电气与信息工程学院,河南 郑州 450001
  • 折叠

摘要

Abstract

Aiming at the problem that traditional frequency hopping network station sorting technology is ineffective under low signal-to-noise ratio conditions and has poor real-time detection performance,this paper proposes a shortwave frequency hop-ping signal sorting algorithm based on the improved YOLOv8(You Only Look Once version 8).First,the short-time Fourier transform is performed on the received aliasing signal to generate a grayscale time-frequency image as the input of the YOLOv8 network model.Secondly,in view of the impact of frequency collisions between aliasing signals such as sweep frequency signals,fixed frequency signals and frequency hopping signals on detection accuracy,the Deform-able Convolutional Net-works v2 is introduced in the C2f layer to improve the generalization ability of network feature ex-traction.Thirdly,the Simam attention mechanism is added to the backbone layer to solve the problem that background noise is easily confused with frequency hopping signals and affects detection accuracy under low signal-to-noise ratio.Finally,the convolutional kernel of Detect module is replaced by Partial Convolution kernel,which reduces the computational complex-ity of the network by 32.18%without the accuracy loss of mAP@0.5 exceeding 0.37%,and improve the inference speed of the network model.Experimental results show that the improved YOLOv8 algorithm proposed in this paper has a separation rate of 97.68%at-5 dB signal-to-noise ratio,and the model has fast convergence and strong robustness.

关键词

跳频信号分选/YOLOv8/DCNv2/SimAM机制/PConv

Key words

frequency hopping signal sorting/YOLOv8/DCNv2/SimAM mechanism/PConv

分类

信息技术与安全科学

引用本文复制引用

朱政宇,赵航冉,王梓晅,王忠勇,巩克现,梁静..一种改进YOLOv8的跳频网台分选算法[J].电子学报,2025,53(2):385-394,10.

基金项目

国家重点研发计划(No.2022YFD2001200) (No.2022YFD2001200)

国家自然科学基金(No.61922072) (No.61922072)

河南省高校科技创新人才支持计划(No.23HASTIT019) (No.23HASTIT019)

河南省自然科学基金(No.232300421097) (No.232300421097)

东南大学移动通信国家重点实验室开放课题(No.2023D11) (No.2023D11)

西安电子科技大学空天地一体化综合业务网全国重点实验室(No.ISN25-24) National Key Research and Development Program of China(No.2022YFD2001200) (No.ISN25-24)

National Natural Science Foundation of China(No.61922072) (No.61922072)

Program for Science&Technology Innovation Talents in Universi-ties of Henan Province(No.23HASTIT019) (No.23HASTIT019)

Natural Science Foundation of Henan Province(No.232300421097) (No.232300421097)

Open Re-search Fund of National Mobile Communications Research Laboratory Southeast University(No.2023D11) (No.2023D11)

Program for Science&Technology Innovation Talents in Universities of Henan Province(No.ISN25-24) (No.ISN25-24)

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