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ISAR Imaging of Object with Varied Rotation Rate by Polynomial Coefficients

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Communications, Signal Processing, and Systems (CSPS 2017)

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 463))

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Abstract

The new technique of inverse synthetic aperture radar (ISAR) imaging for object with varied rotation rate is introduced. It is assumed that the polynomial phase signal (PPS) model is appropriate for the radar echo signal, and the radar image could be achieved via the polynomial coefficients. Here, the radar echo signal is modeled as PPS with order three, and the polynomial coefficients are estimated by the improved form of Chirplet decomposition. Numerical results show the correctness for the proposed technique.

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Acknowledgements

The work is supported by the National Natural Science Foundation of China under grant 61622107 and 61471149.

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Authors and Affiliations

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

    Yong Wang, Bingren Ji, Bin Zhao & Rongqing Xu

Authors
  1. Yong Wang
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  2. Bingren Ji
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  3. Bin Zhao
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  4. Rongqing Xu
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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, Texas, USA

    Qilian Liang

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

    Jiasong Mu

  3. Harbin Institute of Technology, Harbin, Heilongjiang, China

    Min Jia

  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

    Xuhong Feng

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

    Baoju Zhang

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© 2019 Springer Nature Singapore Pte Ltd.

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Wang, Y., Ji, B., Zhao, B., Xu, R. (2019). ISAR Imaging of Object with Varied Rotation Rate by Polynomial Coefficients. In: Liang, Q., Mu, J., Jia, M., Wang, W., Feng, X., Zhang, B. (eds) Communications, Signal Processing, and Systems. CSPS 2017. Lecture Notes in Electrical Engineering, vol 463. Springer, Singapore. https://doi.org/10.1007/978-981-10-6571-2_130

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  • DOI: https://doi.org/10.1007/978-981-10-6571-2_130

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-6570-5

  • Online ISBN: 978-981-10-6571-2

  • eBook Packages: EngineeringEngineering (R0)

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