On numerical simulation of high-speed CCD/CMOS-based wavefront sensors in adaptive optics

Abstract

Wavefront sensors, which use solid-state CCD or CMOS photosensors, are sources of errors in adaptive optic systems. Inaccuracy in the detection of wavefront distortions introduces considerable errors into wavefront reconstruction and leads to overall performance degradation of the adaptive optics system. The accuracy of wavefront sensors is significantly affected by photosensor noise. Thus, it is crucial to formulate high-level photosensor models that enable adaptive optic engineers to simulate realistic effects of noise from wavefront sensors. However, the complexity of solid-state photosensors and multiple noise sources makes it difficult to formulate an adequate model of the photosensor. Moreover, the characterisation of the simulated sensor and comparison with real hardware is often incomplete due to lack of comprehensive standards and guidelines. Owe to these difficulties, engineers work with oversimplified models of the wavefront sensors and consequently have imprecise numerical simulation results. The paper presents an approach for the modelling of noise sources for CCD and CMOS sensors that are used for wavefront sensing in adaptive optics. Both dark and light noise such as fixed pattern noise, photon shot noise, and read noises, as well as, charge-to-voltage noises are described. Procedures for characterisation of both light and dark noises of the simulated photosensors are provided. Numerical simulation results of a photosensor for a high-frame rate Shack-Hartmann wavefront sensor are presented.

Influence of photosensor noise on accuracy of cost-effective Shack-Hartmann wavefront sensors

“…22 Our numerical experiments are aimed in study of a cost-effective wavefront sensor, and for that reason, we simulate CMOS sensors using previously developed high-level model. 18 The model consists of the photon shot noise, the photo response non-uniformity (PRNU/gain FPN), the read noise (includes the dark current, the dark shot noise, the dark FPN, the sense node reset noise, the source follower noise) and ADC quantisation noise. The photosensor is assumed to have 5.00μm pixels with the pixel fill factor of 50%, quantum efficiency of 60%, and full well of 20000 e − .…”

“…Therefore, we used the previously developed comprehensive model of the photosensor. 18 First, the dependency of centroids coordinate from the focal distance of the lenslets was evaluated. After the focus length for the simulations was chosen, the pixelisation error impact on the centroiding was evaluated.…”

“…CMOS photosensor on the centroiding robustness in the Shack-Hartmann wavefront sensor is presented. For the numerical simulations, a comprehensive mathematical model of photosensor's noise 18 was used. The influence of light and dark noises as well as pixelisation factor has been assessed.…”

Scene-based non-uniformity correction: From algorithm to implementation on a smart camera

“…It includes offset FPN and gain FPN. First of all, offset FPN can be defined as a dark signal non-uniformity, which is the offset from the average dark current across the imaging array in the absence of light [8]. It is independent of pixel signal and fixed from frame to frame for a given sensor.…”

“…Since such defects affect all the pixels of a column, column FPN appears as stripes in the image leading to significant image quality degradation. Secondly, gain FPN, which is not cancelled by CDS, is defined as the spatial variation in pixel output values under uniform illumination due to pixel-to-pixel mismatches [8]. Gain FPN is difficult to correct and for years, it was one of the major CMOS imager's disadvantages [11] because it increases with illumination and exponentially increases with temperature.…”