Design of a Near-Field Synthetic Aperture Radar Imaging System Based on Improved RMA

被引:0
作者
Li, Yongcheng [1 ]
Xu, Huaqiang [1 ]
Xu, Jiawei [1 ]
Chen, Hao [1 ]
An, Qiying [1 ]
Hou, Kangming [1 ]
Wang, Jingjing [1 ]
机构
[1] Shandong Normal Univ, Sch Phys & Elect, Jinan 250358, Peoples R China
基金
中国国家自然科学基金;
关键词
near field; SAR; IMRMA; high resolution; coverings; VNA; RANGE MIGRATION ALGORITHM;
D O I
10.3390/rs16173342
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Traditional near-field synthetic aperture radar (SAR) imaging algorithms reveal target features by exploiting signal amplitude and phase information. However, electromagnetic wave propagation is constrained by short distance. Therefore, the spherical wave approximation needs to be considered. In addition, it is also limited by equipment ambient noise, azimuth-distance coupling, wave scattering, and transmission power. Both the amplitude and phase of the signal suffer from the interference of multiple clutter, so they cannot be effectively utilized. To address these issues, this paper introduces a covering penetration detection system based on an improved Range Migration Algorithm (IMRMA) imaging method. Firstly, the proposed method minimizes interferences from the front end of the system using an optimized window to balance denoising and information preservation. Next, interval non-uniform interpolation, instead of Stolt interpolation decoupling, is employed to reduce the computational overhead significantly. To minimize the effects due to wave scattering and propagation loss, distance information is enhanced using amplitude and phase compensation. This reduces scattering effects and enhances image quality. An experimental system is constructed based on a vector network analyzer (VNA) to image the target. The proposed method takes about half the time of traditional RMA. The PSNR in the chunky bowl experiment is higher than 14 dB, which is higher than all the compared methods in the paper. The test results show that the designed system and the reported method can effectively achieve high-resolution images by strengthening the target intensity and suppressing the environmental artifacts.
引用
收藏
页数:25
相关论文
共 42 条
  • [1] Fast Fourier-Based Implementation of Synthetic Aperture Radar Algorithm for Multistatic Imaging System
    Abbasi, Mehryar
    Shayei, Ali
    Shabany, Mahdi
    Kavehvash, Zahra
    [J]. IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, 2019, 68 (09) : 3339 - 3349
  • [2] Microwave Imaging in Security-Two Decades of Innovation
    Ahmed, Sherif S.
    [J]. IEEE JOURNAL OF MICROWAVES, 2021, 1 (01): : 191 - 201
  • [3] Detection and Localization of Buried Pipelines Using a 3-D Multistatic Imaging Radar
    Aljurbua, Abdulrahman
    Sarabandi, Kamal
    [J]. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2022, 60
  • [4] Extended Nonlinear Chirp Scaling Algorithm for High-Resolution Highly Squint SAR Data Focusing
    An, Daoxiang
    Huang, Xiaotao
    Jin, Tian
    Zhou, Zhimin
    [J]. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2012, 50 (09): : 3595 - 3609
  • [5] Inverse medium scattering problems for electromagnetic waves
    Bao, G
    Li, PJ
    [J]. SIAM JOURNAL ON APPLIED MATHEMATICS, 2005, 65 (06) : 2049 - 2066
  • [6] Burki J, 2013, 2013 16TH INTERNATIONAL MULTI TOPIC CONFERENCE (INMIC), P207, DOI 10.1109/INMIC.2013.6731351
  • [7] SAR DATA FOCUSING USING SEISMIC MIGRATION TECHNIQUES
    CAFFORIO, C
    PRATI, C
    ROCCA, E
    [J]. IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS, 1991, 27 (02) : 194 - 207
  • [8] A Subspace Projection Approach for Clutter Mitigation in Holographic Subsurface Imaging
    Chen, Cheng
    He, Zhihua
    Song, Xiaoji
    Liu, Tao
    Su, Yi
    [J]. IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, 2022, 19
  • [9] Near-Field 3D SAR Imaging Using a Scanning Linear MIMO Array With Arbitrary Topologies
    Fan, Bo
    Gao, Jing-Kun
    Li, Hong-Jun
    Jiang, Zhi-Jie
    He, Yan
    [J]. IEEE ACCESS, 2020, 8 : 6782 - 6791
  • [10] Real-Time 3D Microwave Medical Imaging With Enhanced Variational Born Iterative Method
    Fang, Yuan
    Bakian-Dogaheh, Kazem
    Moghaddam, Mahta
    [J]. IEEE TRANSACTIONS ON MEDICAL IMAGING, 2023, 42 (01) : 268 - 280