• Chinese Journal of Quantum Electronics
  • Vol. 39, Issue 6, 927 (2022)
Huimin MA1、*, Lei TAN1, Jinghui ZHANG2, Pengfei ZHANG3, Xiaomei NING1, Haiqiu LIU1, and Yanwei GAO1
Author Affiliations
  • 1[in Chinese]
  • 2[in Chinese]
  • 3[in Chinese]
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    DOI: 10.3969/j.issn.1007-5461.2022.06.007 Cite this Article
    MA Huimin, TAN Lei, ZHANG Jinghui, ZHANG Pengfei, NING Xiaomei, LIU Haiqiu, GAO Yanwei. Review of co-phasing error detection for synthetic aperture imaging system based on deep learning[J]. Chinese Journal of Quantum Electronics, 2022, 39(6): 927 Copy Citation Text show less

    Abstract

    In the optical synthetic aperture imaging system, multiple small aperture telescopes are arranged into a sparse aperture array to increase the equivalent aperture of the system, so as to achieve the high-resolution imaging effect of the large aperture optical system. The detection of co-phasing error between subapertures is an important prerequisite for realizing high-resolution imaging of synthetic aperture systems, and this technology has always been one of the focuses of researchers in this field. The emerging artificial intelligence and big data technology provide a new idea and open up a new direction for the detection of co-phasing error of synthetic aperture imaging system. On the basis of a brief review of the co-phasing error detection methods of synthetic aperture imaging system, the research progress of deep learning technology in co-phasing error detection of synthetic aperture imaging system in recent years is introduced and analyzed, and the future development direction is finally summarized and prospected.
    MA Huimin, TAN Lei, ZHANG Jinghui, ZHANG Pengfei, NING Xiaomei, LIU Haiqiu, GAO Yanwei. Review of co-phasing error detection for synthetic aperture imaging system based on deep learning[J]. Chinese Journal of Quantum Electronics, 2022, 39(6): 927
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