19-element sensorless adaptive optical system based on modified hill-climbing and genetic algorithms

Abstract

A conventional adaptive optical system (AOS) often measures the wavefront slope or curvature straightly by a wavefront sensor. However, another alternative approach allows the design of an AOS without an independent wavefront sensor. This technique detect the image quality affected by phase aberration in laser wavefront rather than measuring the phase aberration itself, and then the image quality is taken as a sharpness metric. When wavefront phase aberration is corrected, the sharpness metric reaches its maximum value. In this paper, a wavefront sensorless adaptive optical system (AOS) has been set up. This system mainly consists of a 19-element piezoelectricity deformable mirror (DM), a high voltage amplifier, a set of 650nm laser, a CCD camera and an industrial computer. The CCD camera is used to measure the light intensity within an aperture of the focus plane, and then this intensity is regarded as the sharpness metric to optimize. A Modified Hill Climbing Algorithm (MHC) and a Genetic Algorithm (GA) are used to control the DM to correct the phase aberrations in this system. Experimental results show that both of these two algorithms can be used successfully in this indirect wavefront measurement AOS. However, the GA can obtain better performance than the MHC. After phase aberrations are corrected, the βfactor are reduced from 5.5 to 1.5 and 1.9, from 30 to 1.2 and 1.4 respectively.