Home Journals Articles Updates About
CN
image
收藏切换
Individual Radiation Source Recognition Based on Multi-resolution Fusion of Radio Frequency Fingerprints
收藏切换
PDF
Jiang YU1, Chuan CHEN1, Yong JIA1, Guangle YAO2, Chen WANG2, Xijuan ZHANG3, Yafeng CHENG4
Telecommunication Engineering | 2025, 65(11) : 1844 - 1850
Less
收藏切换
Telecommunication Engineering | 2025, 65(11): 1844-1850
• Application Fundamental Research and Advanced Technology •
Individual Radiation Source Recognition Based on Multi-resolution Fusion of Radio Frequency Fingerprints
Full
Jiang YU1, Chuan CHEN1, Yong JIA1, Guangle YAO2, Chen WANG2, Xijuan ZHANG3, Yafeng CHENG4
Affiliations
  • 1School of Mechanical and Electrical Engineering，Chengdu University of Technology，Chengdu 610059，China
  • 2School of Computer and Cyber Security，Chengdu University of Technology，Chengdu 610059，China
  • 3Chengdu Aircraft Industrial（Group）Co.，Ltd，Chengdu 610073，China
  • 4Sichuan Koobee Communication Company Limited，Chengdu 644000，China
Published: 2025-11-28 doi: 10.20079/j.issn.1001-893x.240806002
Outline
收藏切换

For the problems of limited expression of characteristic information and low classification accuracy in radiation source classification tasks,an individual radiation source recognition method based on multi-resolution feature fusion is proposed. In this method, the individual characteristics of the radiation source are expressed by using three time-frequency spectra with different resolutions obtained through the Short-Time Fourier Transform. Multi-channel convolutional neural networks are constructed using ResNext50 to extract features with different time-frequency resolutions. A multi-channel feature weighted fusion mechanism is introduced into the network,and the features of different channels are fused by feature weighted fusion, combining the feature information from different resolutions. Experiments show that this method improves the ability to express the subtle fingerprint information of the radiation source signal,and compared with that of the feature layer fusion method and the single feature expression method, the recognition accuracy is improved by 2.15% and 6.8% ,respectively.

individual radiation source recognition  /  RF fingerprint  /  multi-resolution feature fusion  /  short-time Fourier transform
Jiang YU, Chuan CHEN, Yong JIA, Guangle YAO, Chen WANG, Xijuan ZHANG, Yafeng CHENG. Individual Radiation Source Recognition Based on Multi-resolution Fusion of Radio Frequency Fingerprints[J]. Telecommunication Engineering, 2025 , 65 (11) : 1844 -1850 . DOI: 10.20079/j.issn.1001-893x.240806002
Appendix
Less
Year 2025 volume 65 Issue 11
PDF
147
69
Cite this Article
BibTeX
Article Info
doi: 10.20079/j.issn.1001-893x.240806002
  • Receive Date：2024-08-06
  • Online Date：2026-04-15
  • Published：2025-11-28
Article Data
Affiliations
History
  • Received：2024-08-06
  • Revised：2024-10-20
Affiliations
    1School of Mechanical and Electrical Engineering，Chengdu University of Technology，Chengdu 610059，China
    2School of Computer and Cyber Security，Chengdu University of Technology，Chengdu 610059，China
    3Chengdu Aircraft Industrial（Group）Co.，Ltd，Chengdu 610073，China
    4Sichuan Koobee Communication Company Limited，Chengdu 644000，China
References
Share
https://castjournals.cast.org.cn/joweb/dxjs/EN/10.20079/j.issn.1001-893x.240806002
Share to
QR

Scan QR to access full text

Cite this article
BibTeX
Citations
表12种不同金属材料的力学参数
科
Family		 属数
Number of
genus		 种数
Number of
species		 占总种数比例
Percentage of
total species (%)		 属
Genus		 种数
Number of
species		 占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
关闭全屏
  • BibTeX
  • EndNote
  • RefWorks
  • TxT
Links
Articles
Latest Articles
Most Read
Collections
Updates
Events
News
Multimedia
About
About Us
Contact
No. 86 Xueyuan South Road, Haidian District, Beijing
100081
010-62199257
qkjq@cast.org.cn

Copyright © 2025 China Association for Science and Technology. All rights reserved. For all open access content, the relevant licensing terms apply.
Sponsored by the Office of the Leading Group for Cybersecurity and Informatization of CAST, and supported by Science and Technology Review Publishing House