{"title":"Anti-interrupted sampling repeater jamming via linear canonical Wigner distribution lightweight LFM detection","authors":"Jia-Mian Li, Bing-Zhao Li","doi":"10.1016/j.sigpro.2025.110230","DOIUrl":null,"url":null,"abstract":"<div><div>Interrupted sampling repeater jamming (ISRJ) poses a serious threat to radar target detection. Traditional time-frequency (TF) domain anti-jamming methods are prone to TF aliasing in multi-component signal scenarios, and cannot effectively suppress ISRJ with energy close to the real target under low signal-to-noise ratio (SNR) conditions. To address these challenges, this paper proposes an anti-jamming method based on generalized linear canonical Wigner distribution (GLWD) line detection. By setting the parameters reasonably, the TF image of GLWD can have excellent TF resolution and energy concentration, greatly improving the signal separation and SNR. Furthermore, in order to enhance the detection capability of the target LFM signal, the existing mobile line segment detection (M-LSD) is improved and the mobile long line segment detection (M-LLSD) is proposed. M-LLSD can detect the target signal more easily and reduce the sensitivity to the jamming signal, so as to efficiently and accurately extract the TF position information of the target signal. Finally, a TF filter is constructed based on the mapping between GLWD and short-time Fourier transform (STFT), performing filtering in the STFT domain to suppress jamming. Simulations and experiments show that the method can effectively suppress such difficult-to-distinguish jamming and is suitable for real-time radar anti-jamming with good robustness.</div></div>","PeriodicalId":49523,"journal":{"name":"Signal Processing","volume":"239 ","pages":"Article 110230"},"PeriodicalIF":3.6000,"publicationDate":"2025-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Signal Processing","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0165168425003445","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
引用次数: 0
Abstract
Interrupted sampling repeater jamming (ISRJ) poses a serious threat to radar target detection. Traditional time-frequency (TF) domain anti-jamming methods are prone to TF aliasing in multi-component signal scenarios, and cannot effectively suppress ISRJ with energy close to the real target under low signal-to-noise ratio (SNR) conditions. To address these challenges, this paper proposes an anti-jamming method based on generalized linear canonical Wigner distribution (GLWD) line detection. By setting the parameters reasonably, the TF image of GLWD can have excellent TF resolution and energy concentration, greatly improving the signal separation and SNR. Furthermore, in order to enhance the detection capability of the target LFM signal, the existing mobile line segment detection (M-LSD) is improved and the mobile long line segment detection (M-LLSD) is proposed. M-LLSD can detect the target signal more easily and reduce the sensitivity to the jamming signal, so as to efficiently and accurately extract the TF position information of the target signal. Finally, a TF filter is constructed based on the mapping between GLWD and short-time Fourier transform (STFT), performing filtering in the STFT domain to suppress jamming. Simulations and experiments show that the method can effectively suppress such difficult-to-distinguish jamming and is suitable for real-time radar anti-jamming with good robustness.
期刊介绍:
Signal Processing incorporates all aspects of the theory and practice of signal processing. It features original research work, tutorial and review articles, and accounts of practical developments. It is intended for a rapid dissemination of knowledge and experience to engineers and scientists working in the research, development or practical application of signal processing.
Subject areas covered by the journal include: Signal Theory; Stochastic Processes; Detection and Estimation; Spectral Analysis; Filtering; Signal Processing Systems; Software Developments; Image Processing; Pattern Recognition; Optical Signal Processing; Digital Signal Processing; Multi-dimensional Signal Processing; Communication Signal Processing; Biomedical Signal Processing; Geophysical and Astrophysical Signal Processing; Earth Resources Signal Processing; Acoustic and Vibration Signal Processing; Data Processing; Remote Sensing; Signal Processing Technology; Radar Signal Processing; Sonar Signal Processing; Industrial Applications; New Applications.