{"title":"A Low-Rank Modified Imaging Method Based on Gain for Electromagnetic Vortex Radar","authors":"Linrui Fu, Yunxiu Yang, Chang Wang, Qin Shu","doi":"10.1049/ell2.70414","DOIUrl":null,"url":null,"abstract":"<p>This letter addresses the challenges of electromagnetic (EM) vortex radar imaging related to resolution and prior knowledge, proposing an innovative high-resolution imaging algorithm in range and azimuth dimensions. Traditional imaging methods, such as the fast Fourier transform (FFT) and spatial spectrum estimation, are hindered by the imaging quality and the requirement for precise estimation of subspace dimension. To address these, this study proposes a novel 2-dimensional imaging method integrating gain modulation with low-rank modified multiple signal classification (MUSIC) theory. By employing single-rank eigen decomposition, the proposed method eliminates dependence on prior information while optimising computational complexity. The proper gain modulation further enhances the multi-target imaging capabilities. In contrast to FFT and sparse imaging techniques, simulation results and quantitative analyses validated the superior resolution and robustness of the method in complex target scenarios, advancing the EM vortex radar for target observation applications.</p>","PeriodicalId":11556,"journal":{"name":"Electronics Letters","volume":"61 1","pages":""},"PeriodicalIF":0.8000,"publicationDate":"2025-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/ell2.70414","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Electronics Letters","FirstCategoryId":"5","ListUrlMain":"https://ietresearch.onlinelibrary.wiley.com/doi/10.1049/ell2.70414","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
引用次数: 0
Abstract
This letter addresses the challenges of electromagnetic (EM) vortex radar imaging related to resolution and prior knowledge, proposing an innovative high-resolution imaging algorithm in range and azimuth dimensions. Traditional imaging methods, such as the fast Fourier transform (FFT) and spatial spectrum estimation, are hindered by the imaging quality and the requirement for precise estimation of subspace dimension. To address these, this study proposes a novel 2-dimensional imaging method integrating gain modulation with low-rank modified multiple signal classification (MUSIC) theory. By employing single-rank eigen decomposition, the proposed method eliminates dependence on prior information while optimising computational complexity. The proper gain modulation further enhances the multi-target imaging capabilities. In contrast to FFT and sparse imaging techniques, simulation results and quantitative analyses validated the superior resolution and robustness of the method in complex target scenarios, advancing the EM vortex radar for target observation applications.
期刊介绍:
Electronics Letters is an internationally renowned peer-reviewed rapid-communication journal that publishes short original research papers every two weeks. Its broad and interdisciplinary scope covers the latest developments in all electronic engineering related fields including communication, biomedical, optical and device technologies. Electronics Letters also provides further insight into some of the latest developments through special features and interviews.
Scope
As a journal at the forefront of its field, Electronics Letters publishes papers covering all themes of electronic and electrical engineering. The major themes of the journal are listed below.
Antennas and Propagation
Biomedical and Bioinspired Technologies, Signal Processing and Applications
Control Engineering
Electromagnetism: Theory, Materials and Devices
Electronic Circuits and Systems
Image, Video and Vision Processing and Applications
Information, Computing and Communications
Instrumentation and Measurement
Microwave Technology
Optical Communications
Photonics and Opto-Electronics
Power Electronics, Energy and Sustainability
Radar, Sonar and Navigation
Semiconductor Technology
Signal Processing
MIMO