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

^*Corresponding author for this work

School of Electronic and Information Engineering

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

Research output: Contribution to journal › Article › peer-review

8 Scopus citations

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’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.

Original language	English
Article number	153
Pages (from-to)	1-10
Number of pages	10
Journal	Tijdschrift voor Urologie
Volume	2014
Issue number	1
DOIs	https://doi.org/10.1186/1687-6180-2014-153
State	Published - 17 Jan 2014

Keywords

Compressive sensing
General echo model
Maxwell’s equations
Synthetic aperture radar

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10.1186/1687-6180-2014-153

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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",

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

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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

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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

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Keywords

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