光电跟踪与测量技术研究室知识库

Coaxial optical system has a symmetry of revolution. Alignment for this kind of optical system is easy. The desired image quality can be rapidly converged. As for off-Axis optical system, traditional optical alignment method can not be used due to the loss of rotational symmetry. Low initial position accuracy makes installation and adjustment more difficult than usual. In this paper, we aim to solve the alignment problem for off-Axis optical system with the help of machine learning and its powerful numerical fitting ability. We carried out our research on alignment method for an Gregorian off-Axis system. The location of primary mirror is fixed as the optical reference. Alignment process is to adjust posture of secondary mirror to acquire ideal image quality. We use Zemax and Python co-simulation technology to get simulated data. Then multi-layer artificial neural network is utilized to fit the mathematical relationship between misalignments and Zernike coefficients. Given the coefficients, the misalignments can be calculated by the neural network. Finally we conduct alignment experiment to verify the proposed method. The result has proved that this method is a fast and efficient alignment solution for the off-Axis optical systems. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.