A Review on Wavefront Reconstruction Methods

Abstract

Turbulence in the atmosphere in nature leads to the change of local optical path. The imaging wavefront of starlight is constantly distorted and the energy is constantly dissipated, which eventually leads to the blurring of telescope imaging and the degradation of resolution. Therefore, it is necessary to monitor the distorted wavefront in real time through adaptive optics system and correct it through the deformable mirror. The adaptive optics system uses different wavefront reconstruction algorithms to process the output signal from different wavefront sensors and finally recover the wavefront phase. Therefore, a good algorithm for wavefront reconstruction is very important for an optical adaptive system. With the development of interferometer, Hartmann sensor, curvature sensor and pyramid sensor, wavefront reconstruction algorithm has experienced the evolution of slope algorithm, curvature algorithm, algorithm based on light intensity distribution and algorithm based on learning. This paper summarizes the different wavefront fitting algorithms used by different sensors, introducing the advantages and disadvantages of various algorithms, and gives the prospect of the different methods, which has directional reference value for the future development of wavefront reconstruction algorithm.