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Bistatic SAR Imaging Based on Compressive Sensing Approach

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Communications, Signal Processing, and Systems (CSPS 2018)

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 516))

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Abstract

The compressive sensing (CS) technique has been introduced to the field of synthetic aperture radar (SAR) imaging procedure to reduce the amount of measurements. In this letter, a novel algorithm for bistatic SAR imaging based on the CS technique is proposed. The range profile is reconstructed by the Fourier transform, and the azimuth processing is implemented by the CS method consequently. The proposed algorithm can realize the high-quality imaging with limited measurements efficiently for the missing bistatic SAR radar echoes. Results of simulated data demonstrate the validity of the novel approach.

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Acknowledgments

This work was supported in part by the National Natural Science Foundation of China under grant 61471149 and 61622107, and the Fundamental Research Funds for the Central Universities.

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Authors and Affiliations

  1. Research Institute of Electronic Engineering Technology, Harbin Institute of Technology, Harbin, 150001, China

    Yong Wang & Jing Zhou

  2. Beijing Institute of Astronautical System Engineering, Beijing, China

    Hongyuan Zhang

Authors
  1. Yong Wang
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  2. Hongyuan Zhang
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  3. Jing Zhou
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Corresponding author

Correspondence to Yong Wang .

Editor information

Editors and Affiliations

  1. Department of Electrical Engineering, University of Texas at Arlington, Arlington, TX, USA

    Qilian Liang

  2. School of Information and Communication Engineering, Dalian University of Technology, Dalian, China

    Xin Liu

  3. School of Information Science and Technology, Dalian Maritime University, Dalian, China

    Zhenyu Na

  4. College of Electronic and Communication Engineering, Tianjin Normal University, Tianjin, China

    Wei Wang

  5. College of Electronic and Communication Engineering, Tianjin Normal University, Tianjin, China

    Jiasong Mu

  6. College of Electronic and Communication Engineering, Tianjin Normal University, Tianjin, China

    Baoju Zhang

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© 2020 Springer Nature Singapore Pte Ltd.

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Wang, Y., Zhang, H., Zhou, J. (2020). Bistatic SAR Imaging Based on Compressive Sensing Approach. In: Liang, Q., Liu, X., Na, Z., Wang, W., Mu, J., Zhang, B. (eds) Communications, Signal Processing, and Systems. CSPS 2018. Lecture Notes in Electrical Engineering, vol 516. Springer, Singapore. https://doi.org/10.1007/978-981-13-6504-1_95

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  • DOI: https://doi.org/10.1007/978-981-13-6504-1_95

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-13-6503-4

  • Online ISBN: 978-981-13-6504-1

  • eBook Packages: EngineeringEngineering (R0)

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