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Inverse synthetic aperture radar imaging based on sparse signal processing

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Abstract

Based on the measurement model of inverse synthetic aperture radar (ISAR) within a small aspect sector, an imaging method was presented with the application of sparse signal processing. This method can form higher resolution inverse synthetic aperture radar images from compensating incomplete measured data, and improves the clarity of the images and makes the feature structure much more clear, which is helpful for target recognition. The simulation results indicate that this method can provide clear ISAR images with high contrast under complex motion case.

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Authors and Affiliations

  1. Institute of Space Electronic Technology, National University of Defense Technology, Changsha, 410073, China

    Fei Zou  (邹飞) & Xiang Li  (黎湘)

  2. School of Electrical, Electronic and Computer Engineering, The University of Western Australia, Terth, Australia

    Roberto Togneri

Authors
  1. Fei Zou  (邹飞)
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  2. Xiang Li  (黎湘)
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  3. Roberto Togneri
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Corresponding author

Correspondence to Fei Zou  (邹飞).

Additional information

Foundation item: Project supported by the National Natural Science Foundation of China

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Zou, F., Li, X. & Togneri, R. Inverse synthetic aperture radar imaging based on sparse signal processing. J. Cent. South Univ. Technol. 18, 1609–1613 (2011). https://doi.org/10.1007/s11771-011-0879-z

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  • DOI: https://doi.org/10.1007/s11771-011-0879-z

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