Presentation + Paper
10 October 2020 Wavefront measurement based on sparse aperture
Author Affiliations +
Abstract
Large aperture optical system is more and more widely used in astronomy and space optics. With the increase of aperture, the detection methods and instruments are faced with many challenges. It is difficult for traditional full-aperture detection to meet the requirements of modern large-aperture optical system. A sub-aperture inversion method for optical wavefront is proposed. Based on the relationship between the full-aperture wavefront and the sub-aperture wavefront of the optical system, the converting matrix between the sub-aperture Zernike coefficients and the full-aperture Zernike coefficients is established. The full aperture Zernike coefficients are obtained by matrix calculation. Therefore, a small number of discrete sub-aperture wavefront can be used to invert the full aperture wavefront. In this paper, the mathematical model of multi-seed aperture layout is established based on the efficiency and accuracy simultaneously, and the relevant wavefront reconstruction algorithm is discussed. In addition, the optical system detection process is simulated by mathematical simulation, and the results are compared with the results of full-aperture test, so as to verify the technical feasibility of this method. The conclusion is drawed that this method is simple and efficient, and can guarantee high accuracy even when the filling factor is low. It is an ideal method for wavefront measurement of large aperture optical systems.
Conference Presentation
© (2020) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Jingwen Xu, Yun Wang, and Xin Dong "Wavefront measurement based on sparse aperture", Proc. SPIE 11548, Optical Design and Testing X, 115480Q (10 October 2020); https://doi.org/10.1117/12.2573647
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Cited by 1 patent.
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KEYWORDS
Wavefronts

Manufacturing

Mirrors

Astronomical imaging

Astronomy

Mathematical modeling

Reconstruction algorithms

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