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Current progress in sparse signal processing applied to radar imaging

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Abstract

Sparse signal processing is a signal processing technique that takes advantage of signal’s sparsity, allowing signal to be recovered with a reduced number of samples. Compressive sensing, a new branch of the sparse signal processing, has become a rapidly growing research field. Sparse microwave imaging introduces the sparse signal processing theory to radar imaging to obtain new theories, new systems and new methodologies of microwave imaging. This paper first summarizes the latest application of sparse microwave imaging, including Synthetic Aperture Radar (SAR), tomographic SAR and inverse SAR. As sparse signal processing keeps evolving, an avalanche of results have been obtained. We also highlight its recent theoretical advances, including structured sparsity, off-grid, Bayesian approaches, and point out new research directions in sparse microwave imaging.

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Authors and Affiliations

  1. Science and Technology on Microwave Imaging Laboratory, Beijing, 100190, China

    Yao Zhao, BingChen Zhang, Wen Hong & YiRong Wu

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

    Yao Zhao, BingChen Zhang, Wen Hong & YiRong Wu

  3. Beijing Institute of Technology, Beijing, 100081, China

    Jing Feng

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  1. Yao Zhao
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  2. Jing Feng
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  3. BingChen Zhang
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  4. Wen Hong
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  5. YiRong Wu
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Correspondence to Yao Zhao.

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Zhao, Y., Feng, J., Zhang, B. et al. Current progress in sparse signal processing applied to radar imaging. Sci. China Technol. Sci. 56, 3049–3054 (2013). https://doi.org/10.1007/s11431-013-5415-y

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  • DOI: https://doi.org/10.1007/s11431-013-5415-y

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