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Synthetic Aperture Radar Imaging Using Basis Selection Compressed Sensing

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Abstract

A compressed sensing method with basis selection is applied to a millimeter-wave synthetic aperture radar (SAR) imaging system. With a large candidate set of bases to choose from and without any a priori knowledge of the proper basis, the proposed method selects the sparsifying basis during the first few iterations of the L1 optimization according to the information from incomplete measurements and the coherence between the measurement matrix and sparsifying matrices. Several decision metrics can be used to select the basis, including the impulsiveness and Gini index of the available image at the current iteration. The proposed method is tested on two examples: a simulated image and its SAR measurement, and an experimental measurement obtained at 150 GHz via roaster scanning. The results from the simulation and experiment indicate that the proposed algorithm can always find a very good basis from the set of over 270 bases within the first two to five iterations of the L1 optimization.

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Acknowledgments

The work of Dongjie Bi and Yongle Xie was supported by the National Natural Science Foundation of China (61371049) and the Specialized Research Fund for the Doctoral Program of High Education of China (20120185110013). The work of Dongjie Bi was performed during his visit at Missouri University of Science and Technology. The work of Yahong Rosa Zheng was supported in part by the Intelligent Systems Center of Missouri University of Science and Technology, the Inter-Discipline Inter-Campus research program of University of Missouri systems, and the Technology Research Institute of Austin. The authors wish to thank Dr. Kristen Donnell of Missouri University of Science and Technology for providing the SAR measurement data in Fig. 6 and Mr. Zengli Yang of Missouri University of Science and Technology for providing the simulation program that generated Fig. 1a.

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Authors and Affiliations

  1. School of Automation Engineering, University of Electronic Science and Technology of China, Chengdu, 611731, People’s Republic of China

    Dongjie Bi & Yongle Xie

  2. Department of Electrical and Computer Engineering, Missouri University of Science and Technology, Rolla, MO, 65409, USA

    Yahong Rosa Zheng

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  1. Dongjie Bi
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Correspondence to Dongjie Bi.

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Bi, D., Xie, Y. & Zheng, Y.R. Synthetic Aperture Radar Imaging Using Basis Selection Compressed Sensing. Circuits Syst Signal Process 34, 2561–2576 (2015). https://doi.org/10.1007/s00034-015-9974-y

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