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Proceedings Paper

Imaging performance evaluation and phasing error correction of sparse aperture telescope based on small satellites formation
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Paper Abstract

High-resolution space observation is of great importance for scientific and military use. To get higher resolution, a larger imaging aperture is highly required. For example, to obtain one-meter ground sampling distance (GSD) in visible band on geostationary orbit (GEO), the pupil diameter of space telescope is around 25 meters. Trying to fabricate and launch so large monolithic mirror will meet many unconquerable obstacles. A feasible scheme is using sparse aperture imaging technique based on small satellites formation. This paper is focused on a sparse aperture telescope consisting of small sub-telescopes to form a Fizeau imaging interferometer. Each sub-telecope is based on a small satellite. Imaging performance of an annular structure consisting of 25 sub-apertures is evaluated by simulation. The influence of phasing error (including piston and tip/tilt) of subapertures on image quality is evaluated. The co-phasing error budget of sparse aperture telescope dependent on field of view is also analyzed. A co-phasing error detection and correction method based on wavefront sensorless adaptive optics (WSLAO) is proposed at last.

Paper Details

Date Published: 12 March 2020
PDF: 8 pages
Proc. SPIE 11434, 2019 International Conference on Optical Instruments and Technology: Optical Systems and Modern Optoelectronic Instruments, 114340M (12 March 2020); doi: 10.1117/12.2543189
Show Author Affiliations
Ming Li, China Academy of Space Technology (China)
Zhiqiang Zhou, Beijing Institute of Technology (China)
Hongxi Ren, Beijing Institute of Technology (China)
Bing Dong, Beijing Institute of Technology (China)
Xin Wang, China Academy of Launch Vehicle Technology (China)


Published in SPIE Proceedings Vol. 11434:
2019 International Conference on Optical Instruments and Technology: Optical Systems and Modern Optoelectronic Instruments
Juan Liu; Baohua Jia; Xincheng Yao; Yongtian Wang; Takanori Nomura, Editor(s)

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