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Proceedings Paper

Wavefront reconstruction with total-least square method in an adaptive optic system with HS wavefront sensor
Author(s): Rujian Xiang; Kai Zhang; Jing Wu
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Paper Abstract

Adaptive optic systems with HS Wave Front Sensor (WFS) and Deformable Mirror (DM) to compensate the aberration are used to improve the imaging quality and the far field quality laser beam widely, to get the correction driver vector that the deformable mirror needed to produce the conjugated reflecting surface, the matrix equation A⋅ x =ϕ should be solved. The least square method is the most choice used to solve the equation, but the result of the least square consider only about the error of vector ϕ , the solution vector x is no longer suitable while the response matrix A contain any error. A new method base on the total-least square to reconstruct the wavefront is presented, different from the traditional wavefront reconstructing with the least square method, the TLS method takes into account not only the error of vector ϕ , but also the error about the response function matrix A. For testing the characteristics of the solution vector x with the TLS method, an Adaptive Optical (AO) system with 67 actuators DM and 40x40 sub-apertures Hartmann-Shack (HS) WFS is used to simulate the wavefront reconstructing process, and result of simulation and experiments show that the driver vector calculated with TLS method is more stably and the wavefront aberration residual is more reasonable.

Paper Details

Date Published: 3 February 2015
PDF: 9 pages
Proc. SPIE 9255, XX International Symposium on High-Power Laser Systems and Applications 2014, 92553B (3 February 2015); doi: 10.1117/12.2065446
Show Author Affiliations
Rujian Xiang, China Academy of Engineering Physics (China)
Kai Zhang, China Academy of Engineering Physics (China)
Jing Wu, China Academy of Engineering Physics (China)

Published in SPIE Proceedings Vol. 9255:
XX International Symposium on High-Power Laser Systems and Applications 2014
Chun Tang; Shu Chen; Xiaolin Tang, Editor(s)

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