Hybrid algorithm in phase diversity wavefront sensing

Xin Wang; Dazun Zhao; Heng Mao; Xiao Wang

doi:10.1117/12.831453

5 May 2009 Hybrid algorithm in phase diversity wavefront sensing

Xin Wang, Dazun Zhao, Heng Mao, Xiao Wang

Proceedings Volume 7281, 4th International Symposium on Advanced Optical Manufacturing and Testing Technologies: Large Mirrors and Telescopes; 72810S (2009) https://doi.org/10.1117/12.831453
Event: AOMATT 2008 - 4th International Symposium on Advanced Optical Manufacturing, 2008, Chengdu, Chengdu, China

Abstract

Phase diversity (PD), proposed by Gonsalves, is a kind of wavefront sensing technique based on measurement of two or more images of object. The optical system involved is relatively simple. It makes use of the methods of optimization and image processing, which can jointly estimate phase aberration as well as object itself simultaneously. The most significant characteristic of this technique is that it works well with extended scenes. Steepest descent method and conjugate gradient method both are preferable algorithms for nonlinear optimization. As a matter of fact, any one of two methods has some limitations. Steepest descent method is a local property and conjugate gradient method's convergence rate is slow. Combining two methods to develop a mixed algorithm, we can avoid entrapping into a local minimum and raise global convergence rate. Simulation results demonstrate that the hybrid algorithm has the features of quick convergence rate, comparatively large convergence range, which make the method of phase diversity remarkably robust and numerically efficient.

Citation Download Citation

Xin Wang, Dazun Zhao, Heng Mao, and Xiao Wang "Hybrid algorithm in phase diversity wavefront sensing", Proc. SPIE 7281, 4th International Symposium on Advanced Optical Manufacturing and Testing Technologies: Large Mirrors and Telescopes, 72810S (5 May 2009); https://doi.org/10.1117/12.831453

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