Compressive sensing imaging for general synthetic aperture radar echo model based on Maxwell's equations

被引：2
|
作者：
Sun, Bing [1 ,2 ]
Cao, Yufeng [2 ,3 ]
Chen, Jie [1 ]
Li, Chunsheng [1 ]
Qiao, Zhijun [2 ]
机构：
[1] Beihang Univ, Sch Elect & Informat Engn, Beijing 100191, Peoples R China
[2] Univ Texas Pan Amer, Dept Math, Edinburg, TX 78539 USA
[3] Washington State Univ, Dept Math, Pullman, WA 99163 USA
来源：
EURASIP JOURNAL ON ADVANCES IN SIGNAL PROCESSING | 2014年
关键词：
Compressive sensing; General echo model; Maxwell's equations; Synthetic aperture radar; SIGNAL RECOVERY;
D O I：
10.1186/1687-6180-2014-153
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：
A general echo model is derived for the synthetic aperture radar (SAR) imaging with high resolution based on the scalar form of Maxwell's equations. After analyzing the relationship between the general echo model in frequency domain and the existing model in time domain, a compressive sensing (CS) matrix is constructed from random partial Fourier matrices for processing the range CS SAR imaging. Simulations validate the orthogonality of the proposed CS matrix and the feasibility of CS SAR imaging based on the general echo model.
引用
下载
收藏
页码：1 / 10
页数：10
相关论文
共 50 条
  • [31] A Novel Algorithm for Synthetic Aperture Radar Imaging Based on Compressed Sensing
    Bu, Hongxia
    Bai, Xia
    Tao, Ran
    2010 IEEE 10TH INTERNATIONAL CONFERENCE ON SIGNAL PROCESSING PROCEEDINGS (ICSP2010), VOLS I-III, 2010, : 2210 - 2213
  • [32] A Study of Synthetic Aperture Radar Imaging with Compressed Sensing
    Wen, Bihan
    Lu, Yilong
    2012 IEEE ASIA-PACIFIC CONFERENCE ON ANTENNAS AND PROPAGATION (APCAP), 2012, : 325 - 326
  • [33] Novel compressive sensing-based Dechirp-Keystone algorithm for synthetic aperture radar imaging of moving target
    Yang, Jiefang
    Zhang, Yunhua
    IET RADAR SONAR AND NAVIGATION, 2015, 9 (05): : 509 - 518
  • [34] A reconstruction algorithm with Bayesian compressive sensing for synthetic aperture radar images
    Hou, Xingsong
    Zhang, Lan
    Xiao, Lin
    Hsi-An Chiao Tung Ta Hsueh/Journal of Xi'an Jiaotong University, 2013, 47 (08): : 74 - 79
  • [35] One-bit compressive sensing with time-varying thresholds in synthetic aperture radar imaging
    Demir, Mehmet
    Ercelebi, Ergun
    IET RADAR SONAR AND NAVIGATION, 2018, 12 (12): : 1517 - 1526
  • [36] Multi-Channel Synthetic Aperture Radar Imaging of Ground Moving Targets Using Compressive Sensing
    Xu, Gang
    Liu, Yanyang
    Xing, Mengdao
    IEEE ACCESS, 2018, 6 : 66134 - 66142
  • [37] GNSS-based Bistatic Synthetic Aperture Radar Image Formation via Compressive Sensing
    Dai, Chunyang
    Zhou, Liangjiang
    Liang, Xingdong
    Wu, Yirong
    PIERS 2013 STOCKHOLM: PROGRESS IN ELECTROMAGNETICS RESEARCH SYMPOSIUM, 2013, : 1928 - 1932
  • [38] Compressive Synthetic Aperture Radar Imaging and Autofocusing by Augmented Lagrangian Methods
    Gungor, Alper
    Cetin, Mujdat
    Guven, H. Emre
    IEEE TRANSACTIONS ON COMPUTATIONAL IMAGING, 2022, 8 : 273 - 285
  • [39] Aperture-Synthesis Radar Imaging With Compressive Sensing for Ionospheric Research
    Hysell, D. L.
    Sharma, P.
    Urco, M.
    Milla, M. A.
    RADIO SCIENCE, 2019, 54 (06) : 503 - 516
  • [40] Compressive sensing-based inverse synthetic radar imaging imaging from incomplete data
    Tomei, Sonia
    Bacci, Alessio
    Giusti, Elisa
    Martorella, Marco
    Berizzi, Fabrizio
    IET RADAR SONAR AND NAVIGATION, 2016, 10 (02): : 386 - 397
12345