WANG Baoping, ZHANG Yan, FANG Yang, SONG Zuxun. Parametric Narrow-Band InISAR 3D Imaging Based on Compressed Sensing[J]. Chinese Journal of Electronics, 2020, 29(3): 508-514. doi: 10.1049/cje.2020.03.006
Citation: WANG Baoping, ZHANG Yan, FANG Yang, SONG Zuxun. Parametric Narrow-Band InISAR 3D Imaging Based on Compressed Sensing[J]. Chinese Journal of Electronics, 2020, 29(3): 508-514. doi: 10.1049/cje.2020.03.006

Parametric Narrow-Band InISAR 3D Imaging Based on Compressed Sensing

doi: 10.1049/cje.2020.03.006
Funds:  This work is supported by the National Natural Science Foundation of China (No.61472324).
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  • Corresponding author: ZHANG Yan (corresponding author) was born in 1991. He received his M.S. degree in electronic and communication engineering (NWPU). He is a Ph.D. candidate of department of Electronics and Information, NWPU. His research interests include imaging processing and radar imaging. (Email:yan jh@foxmail.com)
  • Received Date: 2019-01-28
  • Rev Recd Date: 2019-10-31
  • Publish Date: 2020-05-10
  • For muti-scatter point target and undersampled data, tradintional imaging method has a poor precision for imaging result and spin angular velocity. In view of the above problems, this paper proposes a narrow-band Interferometric inverse synthetic aperture radar(InISAR) 3-dimensional(3D) Compressed sensing imaging method based on the joint spin angle velocity error parameter estimation. First, a sparse model of narrow-band spin target is constructed. Then, the image entropy is used as the criterion function to search the optimal angle velocity by the joint reconstruction iteration. Finally, the image of the target is obtained by interference processing. The simulation results show that compared with the traditional method, the estimation of spin angular velocity and the imaging result are more accurate in proposed method.
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