High-Resolution ISAR Imaging by Exploiting Sparse Apertures

  title={High-Resolution ISAR Imaging by Exploiting Sparse Apertures},
  author={Lei Zhang and Zhi-jun Qiao and Meng-dao Xing and Jian-Lian Sheng and Rui Guo and Zheng Bao},
  journal={IEEE Transactions on Antennas and Propagation},
Compressive sensing (CS) theory indicates that the optimal reconstruction of an unknown sparse signal can be achieved from limited noisy measurements by solving a sparsity-driven optimization problem. For inverse synthetic aperture radar (ISAR) imagery, the scattering field of the target is usually composed of only a limited number of strong scattering centers, representing strong spatial sparsity. This paper derives a new autofocus algorithm to exploit the sparse apertures (SAs) data for ISAR… CONTINUE READING
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