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An Improved Omega-K SAR Imaging Algorithm Based on Sparse Signal Recovery

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Intelligent Computing (SAI 2020)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1229))

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Abstract

In this paper, an improved Omega-K SAR imaging algorithm is proposed by replacing inverse fast fourier transform with reweighted \( L_{1} \)-norm minimization method and iteratively reweighted least squares method in Omega-K algorithm. Given the advantages of sparse signal recovery, our method can yield lower sidelobes, better resolution and smaller noise. The results of simulated signals and real SAR data show that the proposed algorithms have better performance than Omega-K algorithm.

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Author information

Authors and Affiliations

  1. Beihang University, Beijing, 100191, China

    Shuang Wang, Huaping Xu & Jiawei Zhang

  2. China Agricultural University, Beijing, China

    Boyu Wang

Authors
  1. Shuang Wang
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  2. Huaping Xu
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  3. Jiawei Zhang
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  4. Boyu Wang
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Corresponding author

Correspondence to Shuang Wang .

Editor information

Editors and Affiliations

  1. Faculty of Science and Engineering, Saga University, Saga, Japan

    Kohei Arai

  2. The Science and Information (SAI) Organization, Bradford, West Yorkshire, UK

    Supriya Kapoor

  3. The Science and Information (SAI) Organization, Bradford, West Yorkshire, UK

    Rahul Bhatia

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Wang, S., Xu, H., Zhang, J., Wang, B. (2020). An Improved Omega-K SAR Imaging Algorithm Based on Sparse Signal Recovery. In: Arai, K., Kapoor, S., Bhatia, R. (eds) Intelligent Computing. SAI 2020. Advances in Intelligent Systems and Computing, vol 1229. Springer, Cham. https://doi.org/10.1007/978-3-030-52246-9_25

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