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]µr a d. 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.
ABSTRACT
In order to improve the alignment accuracy of a Cassegrain system, to the best of our knowledge, a novel computer-aided alignment method based on torque sensitivity is proposed. Different from the traditional position sensitivity curve guiding scheme, the accurate position of the secondary mirror is not necessary while the torque sensitivity curve is generated. By establishing the relationship between the torque of the secondary mirror setting screw and the Zernike coefficients of the system, a practical quantitative alignment scheme for the Cassegrain system can be realized. For a two-mirror Cassegrain optical-mechanical system, an alignment scheme based on torque sensitivity is designed. The results show that the wavefront aberrations of three Cassegrain systems reach 0.0479λ,0.0537λ, and 0.0698λ respectively. It proves that the torque sensitivity curves can well guide the real alignment process.