Fast and accurate wavefront sensing algorithm of Shack-Hartmann sensor for adaptive optics

Jae Eun Yoo; Sung Kie Youn

doi:10.1117/12.734546

18 September 2007 Fast and accurate wavefront sensing algorithm of Shack-Hartmann sensor for adaptive optics

Jae Eun Yoo, Sung Kie Youn

Proceedings Volume 6691, Astronomical Adaptive Optics Systems and Applications III; 66910J (2007) https://doi.org/10.1117/12.734546
Event: Optical Engineering + Applications, 2007, San Diego, California, United States

Abstract

Adaptive optics is widely used in astronomy. Recently, most of newly built telescopes have adaptive optical systems. In order to apply adaptive optics into astronomical telescope, high-speed wavefront sensing is required. In high-speed operation, exposure time per frame of a sensor is quite short. In this case, optical intensity of one-frame image is pretty low. Thus signal-to-noise ratio of the wavefront sensor is also low. Therefore, in this case, noises such as readout noise and photon noise greatly influence the accuracy of wavefront sensing. The center of mass method is widely used due to its low computational cost. However it is very weak to noise. The correlation method is robust to noise. But the computational cost is expensive. In this paper, Multi-Resolution Correlation method is proposed. This method, by employing multi-resolution images, considerably reduces the computation time when compared to the FFT correlation method. Also the accuracy of Shack-Hartmann wavefront sensor using the proposed algorithm is proved to be almost same as that of the conventional correlation method. The verification is done through the simulation.

Citation Download Citation

Jae Eun Yoo and Sung Kie Youn "Fast and accurate wavefront sensing algorithm of Shack-Hartmann sensor for adaptive optics", Proc. SPIE 6691, Astronomical Adaptive Optics Systems and Applications III, 66910J (18 September 2007); https://doi.org/10.1117/12.734546

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KEYWORDS

Wavefront sensors

Wavefronts

Adaptive optics

Sensors

Signal to noise ratio

Monte Carlo methods

Point spread functions

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