Generalized Phase Diversity Wavefront Sensing Based on Stochastic Parallel Optimization Algorithm
Main methods on phase retrieval of GPD (Generalized Phase Diversity) wavefront sensor are based on GS (Gerchberg-Saxton) iteration or its derivations, which do not make use of peculiarities of the sensor adequately and have heavy computation.We first decompose the output signal of sensor by Zernike modes and then use SPGD (Stochastic Parallel Gradient Descent) to search the optimum solution.Two different phase screens are used to investigate the phase retrieval method.Simulation results show the method we put forward can correctly restore the phase from the output signal of the GPD wavefront sensor for randomly generated distorted wavefronts and is easy to implement because Zernike modes can be obtained or calculated in advance, which offers the theory basis for further research on GPD wavefront sensor and its real applications.
Generalized phase diversity Wavefront sensing Phase retrieval Stochastic parallel gradient descent
Huizhen Yang Yaoqiu Li
School of Electronic Engineering,Huaihai Institute of Technology,Lianyungang 222005,China
国际会议
International Conference on Advances in Engineering 2011(2011年工程研究进展国际学术会议 ICAE2011)
南京
英文
43-47
2011-12-17（万方平台首次上网日期，不代表论文的发表时间）