An in-orbit correction method based on CNN for the figure errors and component misalignments of TMA telescope

Bingdao Li; Xiaofang Zhang; Yun Gu; Xinqi Hu

doi:10.1117/12.2643878

20 December 2022 An in-orbit correction method based on CNN for the figure errors and component misalignments of TMA telescope

Bingdao Li, Xiaofang Zhang, Yun Gu, Xinqi Hu

Author Affiliations +

Proceedings Volume 12315, Optical Design and Testing XII; 123150T (2022) https://doi.org/10.1117/12.2643878
Event: SPIE/COS Photonics Asia, 2022, Online Only

Abstract

To realize the fast and simple in-orbit aberration correction of TMA telescope, an aberration correction method based on Convolutional Neural Network (CNN) is proposed. CNN is trained to establish the relationship between the defocus point spread function and the misalignments of the secondary mirror. The wavefront aberration caused by the figure errors of the primary mirror and the misalignments of the secondary mirror and the tertiary mirror can be compensated by adjusting the secondary mirror according to the outputs of the well-trained CNN (named as Cor-Net). This method can correct the system aberration quickly and the RMS of the system wavefront aberration is reduced from about 1.5 λ to 0.1 λ by only three correction cycles.

Conference Presentation

Citation Download Citation

Bingdao Li, Xiaofang Zhang, Yun Gu, and Xinqi Hu "An in-orbit correction method based on CNN for the figure errors and component misalignments of TMA telescope", Proc. SPIE 12315, Optical Design and Testing XII, 123150T (20 December 2022); https://doi.org/10.1117/12.2643878

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