A Compressive Sensing-Based Approach for Millimeter-Wave Imaging Compatible with Fourier-Based Image Reconstruction Techniques

被引:0
作者
Molaei, Amir Masoud [1 ]
Kumar, Rupesh [1 ]
Hu, Shaoqing [2 ]
Skouroliakou, Vasiliki [1 ]
Fusco, Vincent [1 ]
Yurduseven, Okan [1 ]
机构
[1] Queens Univ Belfast, Inst Elect Commun & Informat Technol ECIT, Belfast, Antrim, North Ireland
[2] Brunel Univ London, Dept Elect & Elect Engn, London, England
来源
2022 23RD INTERNATIONAL RADAR SYMPOSIUM (IRS) | 2022年
关键词
Compressive sensing; experimental results; Fourier-based techniques; mm-wave imaging; RADAR; ALGORITHM;
D O I
暂无
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
The unique characteristics of the millimeter-wave (mmW) frequency band have led to its widespread use in various fields such as communications, imaging, and wireless sensing. This paper addresses two different mmW imaging structures, monostatic and multistatic, in the face of a sparse spatial sampling scenario. By using compressive sensing theory, a solution for image reconstruction, consistent with fast Fourierbased techniques, is presented with compressed data obtained from monostatic imaging. This solution is then generalized to a multiple-input multiple-output (MIMO) imaging case using a multistatic-to-monostatic conversion. Reconstructed images from numerical and experimental data show the satisfactory performance of the presented approach.
引用
收藏
页码:87 / 91
页数:5
相关论文
共 50 条
  • [21] Robust Compressive Two-Dimensional Near-Field Millimeter-Wave Image Reconstruction in Impulsive Noise
    Lyu, Jue
    Bi, Dongjie
    Li, Xifeng
    Xie, Yongle
    IEEE SIGNAL PROCESSING LETTERS, 2019, 26 (04) : 567 - 571
  • [22] Compressive Sensing based Channel Estimation for Millimeter Wave MIMO
    Kirthiga, S.
    PROCEEDINGS OF 2017 IEEE INTERNATIONAL CONFERENCE ON CIRCUIT ,POWER AND COMPUTING TECHNOLOGIES (ICCPCT), 2017,
  • [23] Image Super-Resolution Through Compressive Sensing-based Recovery
    Zanddizari, Hadi
    Dey, Ankita
    Rajan, Sreeraman
    2021 43RD ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE & BIOLOGY SOCIETY (EMBC), 2021, : 4006 - 4010
  • [24] Compressive Sensing Operator Design and Optimization for Wideband 3-D Millimeter-Wave Imaging
    Bi, Dongjie
    Li, Xifeng
    Xie, Xuan
    Xie, Yongle
    Zheng, Yahong Rosa
    IEEE TRANSACTIONS ON MICROWAVE THEORY AND TECHNIQUES, 2022, 70 (01) : 542 - 555
  • [25] Multidimensional dictionary learning algorithm for compressive sensing-based hyperspectral imaging
    Zhao, Rongqiang
    Wang, Qiang
    Shen, Yi
    Li, Jia
    JOURNAL OF ELECTRONIC IMAGING, 2016, 25 (06)
  • [26] A fast and efficient approach to color-image encryption based on compressive sensing and fractional Fourier transform
    Zhang, Di
    Liao, Xiaofeng
    Yang, Bo
    Zhang, Yushu
    MULTIMEDIA TOOLS AND APPLICATIONS, 2018, 77 (02) : 2191 - 2208
  • [27] RESEARCH ON COMPRESSIVE SENSING-BASED 3D IMAGING METHOD APPLIED TO GPR
    Yu Hui-min
    Jiang Song
    MICROWAVE AND OPTICAL TECHNOLOGY LETTERS, 2013, 55 (12) : 2896 - 2901
  • [28] A Fourier-based compressed sensing technique for accelerated CT image reconstruction using first-order methods
    Choi, Kihwan
    Li, Ruijiang
    Nam, Haewon
    Xing, Lei
    PHYSICS IN MEDICINE AND BIOLOGY, 2014, 59 (12) : 3097 - 3119
  • [29] Fast Compressive Sensing-Based SAR Imaging Integrated With Motion Compensation
    Pu, Wei
    Huang, Yulin
    Wu, Junjie
    Yang, Haiguang
    Yang, Jianyu
    IEEE ACCESS, 2019, 7 : 53284 - 53295
  • [30] Compressive Sensing based Image acquisition and Reconstruction analysis
    Ravindranath, Sabbisetti
    Ram, S. R. Nishanth
    Subhashini, S.
    Reddy, A. V. Sesha
    Janarth, M.
    Vignesh, R. Aswath
    Gandhiraj, R.
    Soman, K. P.
    2014 INTERNATIONAL CONFERENCE ON GREEN COMPUTING COMMUNICATION AND ELECTRICAL ENGINEERING (ICGCCEE), 2014,