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A SAR imaging method based on generalized minimax-concave penalty

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References

  1. Zhang B C, Hong W, Wu Y R. Sparse microwave imaging: principles and applications. Sci China Inf Sci, 2012, 55: 1722–1754

    Article  MathSciNet  Google Scholar 

  2. Baraniuk R, Steeghs P. Compressive radar imaging. In: Proceedings of IEEE Radar Conference, Boston, 2007. 128–133

    Google Scholar 

  3. Fang J, Xu Z B, Zhang B C, et al. Fast compressed sensing SAR imaging based on approximated observation. IEEE J Sel Top Appl Earth Observations Remote Sens, 2014, 7: 352–363

    Article  Google Scholar 

  4. Bi H, Zhang B, Zhu X X, et al. Extended chirp scalingbaseband azimuth scaling-based azimuth-range decouple L1 regularization for TOPS SAR imaging via CAMP. IEEE Trans Geosci Remote Sens, 2017, 55: 3748–3763

    Article  Google Scholar 

  5. Quan X Y, Zhang B C, Wang Z D, et al. An efficient data compression technique based on BPDN for scattered fields from complex targets. Sci China Inf Sci, 2017, 60: 109302

    Article  Google Scholar 

  6. Candes E, Tao T. The Dantzig selector: statistical estimation when p is much larger than n. Ann Stat, 2007, 35: 2313–2351

    Article  MathSciNet  Google Scholar 

  7. Selesnick I. Sparse regularization via convex analysis. IEEE Trans Signal Process, 2017, 65: 4481–4494

    Article  MathSciNet  Google Scholar 

  8. Bauschke H H, Combettes P L. Convex Analysis and Monotone Operator Theory in Hilbert Spaces. New York: Springer, 2011

    Book  Google Scholar 

  9. Naidu K. Data dome: full k-space sampling data for high-frequency radar research. Proc SPIE Int Soc Opt Eng, 2004, 5427: 200–207

    Google Scholar 

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Acknowledgements

This work was supported by National Natural Science Foundation of China (Grant No. 61571419).

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Authors and Affiliations

  1. University of Chinese Academy of Sciences, Beijing, 100049, China

    Zhonghao Wei & Bingchen Zhang

  2. Key Laboratory of Technology in Geospatial Information Processing and Application Systems, Institute of Electronics, Chinese Academy of Sciences, Beijing, 100190, China

    Zhonghao Wei

  3. Institute of Electronics, Chinese Academy of Sciences, Beijing, 100190, China

    Zhonghao Wei, Bingchen Zhang & Yirong Wu

Authors
  1. Zhonghao Wei
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  2. Bingchen Zhang
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  3. Yirong Wu
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Correspondence to Zhonghao Wei.

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Wei, Z., Zhang, B. & Wu, Y. A SAR imaging method based on generalized minimax-concave penalty. Sci. China Inf. Sci. 62, 29305 (2019). https://doi.org/10.1007/s11432-018-9464-4

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  • DOI: https://doi.org/10.1007/s11432-018-9464-4

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