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.
High-resolution wavefront reconstruction using the frozen flow hypothesis
AOPC 2017: Space Optics and Earth Imaging and Space Navigation ; 2017 ; Beijing,China
Proc. SPIE ; 10463
2017-10-24
Conference paper
Electronic Resource
English
Fast PSF Reconstruction Using the Frozen Flow Hypothesis
British Library Conference Proceedings | 2010
|Parallel Implementation of a Frozen Flow Based Wavefront Reconstructor
British Library Conference Proceedings | 2014
|Coherent wavefront reconstruction using object statistics
British Library Conference Proceedings | 1995
|Simultaneous High-resolution Optical Wavefront and Flow Diagnostics for High-speed Flows
British Library Conference Proceedings | 2003
|