This paper describes an approach to reconstructing wavefronts on finer grid using the frozen flow hypothesis (FFH), which exploits spatial and temporal correlations between consecutive wavefront sensor (WFS) frames. Under the assumption of FFH, slope data from WFS can be connected to a finer, composite slope grid using translation and down sampling, and elements in transformation matrices are determined by wind information. Frames of slopes are then combined and slopes on finer grid are reconstructed by solving a sparse, large-scale, ill-posed least squares problem. By using reconstructed finer slope data and adopting Fried geometry of WFS, high-resolution wavefronts are then reconstructed. The results show that this method is robust even with detector noise and wind information inaccuracy, and under bad seeing conditions, high-frequency information in wavefronts can be recovered more accurately compared with when correlations in WFS frames are ignored.


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    Title :

    High-resolution wavefront reconstruction using the frozen flow hypothesis


    Contributors:
    Liu, Xuewen (author) / Liang, Yonghui (author) / Liu, Jin (author) / Xu, Jieping (author)

    Conference:

    AOPC 2017: Space Optics and Earth Imaging and Space Navigation ; 2017 ; Beijing,China


    Published in:

    Proc. SPIE ; 10463


    Publication date :

    2017-10-24





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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