Review of co-phasing error detection for synthetic aperture imaging
system based on deep learning

doi:10.3969/j.issn.1007-5461.2022.06.007

Abstract

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.

Key words: tmospheric optics, synthetic aperture, co-phasing error detection, deep learning, convolutional neural network

CLC Number:

O439

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): 927-941.

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Review of co-phasing error detection for synthetic aperture imaging system based on deep learning

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