Affiliation:
1. China Academy of Engineering Physics
2. Sichuan University
Abstract
Optical sparse-aperture systems face severe challenges, including
detecting and correcting co-phase errors. In this study, a search
framework based on fine tuning a pre-trained network is proposed to
analyze the co-phase errors of a Golay3 telescope system. Based on
this, an error compensation control system is established. First, a
hash-like binary code is created by fine-tuning the pre-trained model.
Secondly, a pre-trained network is used to extract the deep features
of the image, and an index database is built between the image
features and the corresponding co-phase error values. Finally, the Top
1-ranked features and corresponding co-phase error values are returned
through the hash-like binary code hierarchical deep search database to
provide driving data for the error correction system. Numerical
simulations and experimental results verify the method’s validity. The
experimental results show that the correction system works well when
the dynamic piston is [−5,5]λ, and the tilt error range is [−15,15]µrad. Compared with existing detection
methods, this method does not require additional optical components,
has a high correction accuracy, and requires a short training time.
Furthermore, it can be used to detect piston and tilt errors
simultaneously.
Funder
Major Science and Technology Projects in
Sichuan Province
Subject
Atomic and Molecular Physics, and Optics,Engineering (miscellaneous),Electrical and Electronic Engineering
Cited by
1 articles.
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