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Piston Error Measurement for Segmented Telescopes with an Artificial Neural Network
2021
Sensors
A piston error detection method is proposed based on the broadband intensity distribution on the image plane using a back-propagation (BP) artificial neural network. By setting a mask with a sparse circular clear multi-subaperture configuration in the exit pupil plane of a segmented telescope to fragment the pupil, the relation between the piston error of segments and amplitude of the modulation transfer function (MTF) sidelobes is strictly derived according to the Fourier optics principle.
doi:10.3390/s21103364
pmid:34066193
fatcat:v74znfjr3jftngenbcejfxfage