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.
When space optical remote sensing system works in orbit, it is easy to be affected by the external environment such as heat, gravity and platform jitter, which makes the position of components such as secondary mirror be misaligned, resulting in the degradation of image quality. The traditional position misalignment detection technology has the disadvantages of complex device, time-consuming calculation and low accuracy. A deep learning method using convolutional neural network (CNN) is proposed to predict the positional misalignment of the secondary mirror directly from the defocus point spread function (PSF). The simulation results show that the system can be restored to the original design state under a small dynamic range of position error simply and quickly, which is a great significance for space remote sensing system in-orbit alignment.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.