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

Bing Sun; Yufeng Cao; Jie Chen; Chunsheng Li; Zhijun Qiao

doi:10.1186/1687-6180-2014-153

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

Bing Sun
, Yufeng Cao
, Jie Chen^*
, Chunsheng Li
, Zhijun Qiao

^*此作品的通讯作者

电子信息工程学院

Beihang University
University of Texas-Pan American
Washington State University Pullman

科研成果: 期刊稿件 › 文章 › 同行评审

8 引用（Scopus）

摘要

Abstract: 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.

源语言	英语
文章编号	153
页（从-至）	1-10
页数	10
期刊	Tijdschrift voor Urologie
卷	2014
期	1
DOI	https://doi.org/10.1186/1687-6180-2014-153
出版状态	已出版 - 17 1月 2014

访问文件

10.1186/1687-6180-2014-153

其它文件与链接

链接到 Scopus 的出版物

引用此

@article{e4257b92319e43249df0571feae3cb4e,

title = "Compressive sensing imaging for general synthetic aperture radar echo model based on Maxwell{\textquoteright}s equations",

abstract = "Abstract: A general echo model is derived for the synthetic aperture radar (SAR) imaging with high resolution based on the scalar form of Maxwell{\textquoteright}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.",

keywords = "Compressive sensing, General echo model, Maxwell{\textquoteright}s equations, Synthetic aperture radar",

author = "Bing Sun and Yufeng Cao and Jie Chen and Chunsheng Li and Zhijun Qiao",

note = "Publisher Copyright: {\textcopyright} 2014, Sun et al.; licensee Springer.",

year = "2014",

month = jan,

day = "17",

doi = "10.1186/1687-6180-2014-153",

language = "英语",

volume = "2014",

pages = "1--10",

journal = "Tijdschrift voor Urologie",

issn = "2211-3037",

publisher = "Springer Science + Business Media",

number = "1",

}

TY - JOUR

T1 - Compressive sensing imaging for general synthetic aperture radar echo model based on Maxwell’s equations

AU - Sun, Bing

AU - Cao, Yufeng

AU - Chen, Jie

AU - Li, Chunsheng

AU - Qiao, Zhijun

PY - 2014/1/17

Y1 - 2014/1/17

N2 - Abstract: 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.

AB - Abstract: 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.

KW - Compressive sensing

KW - General echo model

KW - Maxwell’s equations

KW - Synthetic aperture radar

UR - https://www.scopus.com/pages/publications/84919332082

U2 - 10.1186/1687-6180-2014-153

DO - 10.1186/1687-6180-2014-153

M3 - 文章

AN - SCOPUS:84919332082

SN - 2211-3037

VL - 2014

SP - 1

EP - 10

JO - Tijdschrift voor Urologie

JF - Tijdschrift voor Urologie

IS - 1

M1 - 153

ER -

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

摘要

访问文件

其它文件与链接

指纹

引用此