Shack–Hartmann wavefront sensor based on Kalman filter

Abstract

The Shack–Hartmann wavefront sensor (SHWFS) traditionally employs the center of gravity (CoG), windowing, and thresholding CoG (TCoG) algorithms to measure wavefront aberrations. Nevertheless, these algorithms yield low accuracy in a low signal-to-noise ratio (SNR) environment, and therefore, we propose a measurement algorithm based on the Kalman filter to correct the three algorithms’ centroid position of the Shack–Hartmann spot. When the Euclidean distance between the reference centroid in a sub-aperture and the measurement centroid exceeds a certain threshold, the sub-apertures centroid position is untrusted and must be corrected. Several simulation experiments are conducted in three environments: no noise, Poisson noise, and Gaussian noise; they demonstrate that the proposed algorithm effectively improves the centroid’s accuracy by more than 10% and ensures real-time performance for the adaptive optics system. In addition, experimental results on wavefront reconstruction tasks reveal that our algorithm produces wavefronts close to the original.