Advanced in Radar Signal Processing

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Microwave and Wireless Communications".

Deadline for manuscript submissions: closed (31 March 2023) | Viewed by 1815

Special Issue Editors


E-Mail Website
Guest Editor
National Lab of Radar Signal Processing, Xidian University, Xi’an 710071, China
Interests: target detection and recognition; deep learning; synthetic aperture radar
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
National Lab of Radar Signal Processing, Xidian University, Xi’an 710071, China
Interests: radar imaging; target recognition

Special Issue Information

Dear Colleagues,

Signal processing is the core of the radar techniques. Recent developments in the field has allowed increasing demands of modern radar systems to be met. Advances in the area, especially those specific to future technology, deserve great and continuous attention. The rapid growth of the technology, the availability of enhanced computational resources, the development of new signal processing techniques, and the introduction of artificial intelligence skills have made the radar more effective and more powerful. They have attracted a renewed interest from the worldwide scientific community.

This Special Issue aims to gather the recent research results in the area of radar signal processing techniques. Both the applications in military and civilian fields are welcome. Topics include but are not limited to:

  • SAR/ISAR imaging;
  • target detection and tracking;
  • target recognition and classification;
  • radar image semantic segmentation;
  • radar image change detection;
  • radar image registration;
  • radar image despeckling.

Dr. Ganggang Dong
Dr. Shuai Shao
Guest Editors

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Keywords

  • SAR/ISAR imaging 
  • target detection and tracking 
  • target recognition and classification 
  • radar image semantic segmentation 
  • radar image change detection 
  • radar image registration 
  • radar image despeckling

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Published Papers (1 paper)

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Research

18 pages, 5847 KiB  
Article
Service Performance Evaluation of Operating Loess Railway Tunnel Based on Bayesian Network
by Yandong Yang, Qian Zhang, Fang Xu, Mingyuan Du, Linyan Hou and Lili Hou
Electronics 2023, 12(4), 958; https://doi.org/10.3390/electronics12040958 - 15 Feb 2023
Cited by 4 | Viewed by 1296
Abstract
Due to the particularity of loess engineering geology, loess railway tunnel accidents occur frequently. Based on the theoretical basis of risk management, this study evaluated the service performance of loess railway tunnels. Based on the improved TOPSIS method, the indirect proximity degree of [...] Read more.
Due to the particularity of loess engineering geology, loess railway tunnel accidents occur frequently. Based on the theoretical basis of risk management, this study evaluated the service performance of loess railway tunnels. Based on the improved TOPSIS method, the indirect proximity degree of each risk factor was compared, and the appropriate service performance evaluation index was selected. Based on the ISM model and the causality graph modification method, the dependency relationship between nodes was obtained and the Bayesian network evaluation model was constructed. By constructing the database, the EM algorithm was used for data learning, and the model was trained and verified, and the overall accuracy (ACC) and F1 value are used to comprehensively evaluate the training and prediction effect of the model. Finally, the evaluation model was applied to a tunnel case. The results show that the established Bayesian network model has a high accuracy of 92%, which is easy to operate, effective and practical, and it is also applicable in situations of incomplete index statistical data. Full article
(This article belongs to the Special Issue Advanced in Radar Signal Processing)
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