Modulated-ISRJ rejection using online dictionary learning for synthetic aperture radar imagery

被引:0
|
作者
WEI Shaopeng [1 ,2 ]
ZHANG Lei [3 ]
LU Jingyue [4 ]
LIU Hongwei [2 ]
机构
[1] College of Oceanography and Space Informatics, China University of Petroleum (East China)
[2] School of Electronics Engineering, Xidian University
[3] School of Electronics and Communication Engineering, Shenzhen Campus of Sun Yat-sen University
[4] School of Computer Science and Technology, Xidian University
基金
中国国家自然科学基金;
关键词
D O I
暂无
中图分类号
TN957.52 [数据、图像处理及录取];
学科分类号
080904 ; 0810 ; 081001 ; 081002 ; 081105 ; 0825 ;
摘要
In electromagnetic countermeasures circumstances,synthetic aperture radar(SAR) imagery usually suffers from severe quality degradation from modulated interrupt sampling repeater jamming(MISRJ), which usually owes considerable coherence with the SAR transmission waveform together with periodical modulation patterns. This paper develops an MISRJ suppression algorithm for SAR imagery with online dictionary learning. In the algorithm, the jamming modulation temporal properties are exploited with extracting and sorting MISRJ slices using fast-time autocorrelation. Online dictionary learning is followed to separate real signals from jamming slices. Under the learned representation, time-varying MISRJs are suppressed effectively. Both simulated and real-measured SAR data are also used to confirm advantages in suppressing time-varying MISRJs over traditional methods.
引用
收藏
页码:316 / 329
页数:14
相关论文
共 50 条
  • [1] Modulated-ISRJ Rejection using Online Dictionary Learning for Synthetic Aperture Radar Imagery
    College of Oceanography and Space Informatics, China University of Petroleum , Qingdao
    266580, China
    不详
    710071, China
    不详
    518107, China
    不详
    710071, China
    J Syst Eng Electron, 2024, 2 (316-329):
  • [2] Modulated-ISRJ Rejection using Online Dictionary Learning for Synthetic Aperture Radar Imagery
    Wei, Shaopeng
    Zhang, Lei
    Lu, Jingyue
    Liu, Hongwei
    JOURNAL OF SYSTEMS ENGINEERING AND ELECTRONICS, 2024, 35 (02) : 316 - 329
  • [3] The Development of Deep Learning in Synthetic Aperture Radar Imagery
    Schwegmann, C. P.
    Kleynhans, W.
    Salmon, B. P.
    2017 INTERNATIONAL WORKSHOP ON REMOTE SENSING WITH INTELLIGENT PROCESSING (RSIP 2017), 2017,
  • [4] Inverse Synthetic Aperture Radar Imaging Exploiting Dictionary Learning
    Hu, Changyu
    Wang, Ling
    Loffeld, Otmar
    2018 IEEE RADAR CONFERENCE (RADARCONF18), 2018, : 1084 - 1088
  • [5] Using synthetic aperture radar imagery for flood modelling
    Galy, Hélène
    Sanders, Richard A.
    Transactions in GIS, 2002, 6 (01) : 31 - 42
  • [6] Georeferencing on Synthetic Aperture RADAR imagery
    Esmaeilzade, M.
    Amini, J.
    Zakeri, S.
    INTERNATIONAL CONFERENCE ON SENSORS & MODELS IN REMOTE SENSING & PHOTOGRAMMETRY, 2015, 41 (W5): : 179 - 184
  • [7] AZIMUTHAL AMBIGUITIES IN SYNTHETIC APERTURE SONAR AND SYNTHETIC APERTURE RADAR IMAGERY
    ROLT, KD
    SCHMIDT, H
    IEEE JOURNAL OF OCEANIC ENGINEERING, 1992, 17 (01) : 73 - 79
  • [8] VERY DEEP LEARNING FOR SHIP DISCRIMINATION IN SYNTHETIC APERTURE RADAR IMAGERY
    Schwegmann, C. P.
    Kleynhans, W.
    Salmon, B. P.
    Mdakane, L. W.
    Meyer, R. G. V.
    2016 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS), 2016, : 104 - 107
  • [9] TARGET IDENTIFICATION IN SYNTHETIC APERTURE RADAR IMAGERY USING SYNTHETIC DISCRIMINANT FUNCTIONS
    MUNIPALLI, S
    ROGERS, SK
    MEER, DE
    KABRISKY, M
    BRYANT, M
    MILLIMETER WAVE AND SYNTHETIC APERTURE RADAR, 1989, 1101 : 170 - 182
  • [10] Ship detection using ensemble deep learning techniques from synthetic aperture radar imagery
    Gupta, Himanshu
    Verma, Om Prakash
    Sharma, Tarun Kumar
    Varshney, Hirdesh
    Agarwal, Saurabh
    Pak, Wooguil
    SCIENTIFIC REPORTS, 2024, 14 (01):