Open AccessAdaptive piston correction of sparse aperture systems with stochastic parallel gradient descent algorithm
Author(s) -
Zongliang Xie,
Haotong Ma,
Xiufeng He,
Bo Qi,
Guanghui Ren,
Li Dong,
Yufeng Tan
Publication year - 2018
Publication title -
optics express
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.394
H-Index - 271
ISSN - 1094-4087
DOI - 10.1364/oe.26.009541
Subject(s) - piston (optics) , gradient descent , adaptive optics , computer science , stochastic gradient descent , deformable mirror , aperture (computer memory) , optics , image quality , algorithm , wavefront , physics , artificial intelligence , image (mathematics) , acoustics , artificial neural network
A phased sparse aperture system provides an economic solution to get high resolution images with less volume and weight. The crucial point of such systems is adaptive correction of piston, that is, a close-loop control aiming at stabilizing the optical path differences within a fraction of the wavelength. In this paper, we present an autonomous phasing approach using stochastic parallel gradient descent algorithm through optimization of image quality. The synthetic system can be phased by iteratively commanding piston actuators without any additional optics. Simulations are first performed to test the validity. Then experimental results based on a binocular telescope testbed are presented, showing that our proposed close-loop control of piston correction doesn't only work with both laser and white-light point sources, but also with an extended object.