Improved compressed sensing for highresolution ISAR image reconstruction

For inverse synthetic aperture radar （ISAR）, an ISAR signal in the crossrange direction has the characteristic of sparsity in the azimuth frequency domain. Due to this property, a Fourier basis is adopted as a kind of sparse basis, and high crossrange resolution imaging is achieved by using the comp...

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Bibliographic Details
Published in中国科学通报：英文版 no. 23; pp. 2918 - 2926
Main Author Shunsheng Zhang Bo Xiao Zhulin Zong
Format Journal Article
LanguageEnglish
Published 2014
Subjects
ISAR
传感
压缩
图像重建
稀疏表示
逆合成孔径雷达
雷达信号
高分辨率成像
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Summary:For inverse synthetic aperture radar （ISAR）, an ISAR signal in the crossrange direction has the characteristic of sparsity in the azimuth frequency domain. Due to this property, a Fourier basis is adopted as a kind of sparse basis, and high crossrange resolution imaging is achieved by using the compressed sensing （CS） method. However, the Fourier expanding for signal with finite length will result in energy leaking and spectrum widening. As a result, the Fourier basis cannot obtain the optimum sparse representation for signals of unknown frequencies in most cases. In this paper, we present an improved Fourier basis for sparse representation of the ISAR signal, which is constructed by frequency shift and weighting of the Fourier basis and available to obtain the robust recovery performance via CS. Simulation results show that the improved CS method outperforms conventional CS method that uses the Fourier basis.
Bibliography:11-1785/N
Shunsheng Zhang , Bo Xiao , Zhulin Zong（1 Research Institute of Electronic Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, China;2 Key Laboratory of Integrated Electronic System, Ministry of Education, Chengdu 611731, China）
For inverse synthetic aperture radar （ISAR）, an ISAR signal in the crossrange direction has the characteristic of sparsity in the azimuth frequency domain. Due to this property, a Fourier basis is adopted as a kind of sparse basis, and high crossrange resolution imaging is achieved by using the compressed sensing （CS） method. However, the Fourier expanding for signal with finite length will result in energy leaking and spectrum widening. As a result, the Fourier basis cannot obtain the optimum sparse representation for signals of unknown frequencies in most cases. In this paper, we present an improved Fourier basis for sparse representation of the ISAR signal, which is constructed by frequency shift and weighting of the Fourier basis and available to obtain the robust recovery performance via CS. Simulation results show that the improved CS method outperforms conventional CS method that uses the Fourier basis.
Improved compressed sensing （ICS）;Inverse synthetic aperture radar （ISAR） ;Imagereconstruction ; Improved Fourier basis; Sparse representation
ISSN:1001-6538
1861-9541