Atmospheric turbulence limits the resolving power of astronomical telescopes by distorting the paths of light between distant objects of interest and the imaging camera at the telescope. After many light-years of travel, passing through the turbulence in that last 100km of a photon’s journey results in a blurred image in the telescope, no less than 1” (arc-second) in width. To achieve higher resolutions, corresponding to smaller image widths, various methods have been proposed with varying degrees of effectiveness and practicality.

Space telescopes avoid atmospheric turbulence completely and are limited in resolution solely by the size of their mirror apertures. However, the design and maintenance cost of space telescopes, which increases prohibitively with size, has limited the number of space telescopes deployed for astronomical imaging purposes. Ground based telescopes can be built larger and more cheaply, so atmospheric compensation schemes using adaptive optical cancellation mirrors can be a cheaper substitute for space telescopes.

Adaptive optics is referred to here as the use of electronic control of optical component to modify the phase of an incident ray within an optical system like an imaging telescope. Fast adaptive optics systems operating in real-time can be used to correct the optical aberrations introduced by atmospheric turbulence. To compensate those aberrations, they must first be measured using a wavefront sensor. The wavefront estimate from the wavefront sensor can then be applied, in a closed-loop system, to a deformable mirror to compensate the incoming wavefront.

Many wavefront sensors have been proposed and are in used today in adaptive optics and atmospheric turbulence measurement systems. Experimental results comparing the performance of wavefront sensors have also been published. However, little detailed analyses of the fundamental similarities and differences between the wavefront sensors have been performed.

This study concentrates on fourmain types of wavefront sensors, namely the Shack-Hartmann, pyramid, geometric, and the curvature wavefront sensors, and attempts to unify their description within a common framework. The quad-cell is a wavefront slope detector and is first examined as it lays the groundwork for analysing the Shack-Hartmann and pyramid wavefront sensors.

The quad-cell slope detector is examined, and a new measure of performance based on the Strehl ratio of the focal plane image is adopted. The quad-cell performance based on the Strehl ratio is compared using simulations against the Cramer-Rao bound, an information theoretic or statistical limit, and a polynomial approximation. The effects of quad-cell modulation, its relationship to extended objects, and the effect on performance are also examined briefly.

In the Shack-Hartmann and pyramid wavefront sensor, a strong duality in the imaging and aperture planes exists, allowing for comparison of the performance of the two wavefront sensors. Both sensors subdivide the input wavefront into smaller regions, and measure the local slope. They are equivalent in every way except for the order in which the subdivision and slope measurements were carried out. We show that this crucial difference leads to a theoretically higher performance from the pyramid wavefront sensor. We also presented simulations showing the trade-off between sensor precision and resolution.

The geometric wavefront sensor can be considered to be an improved curvature wavefront sensor as it uses a more accurate algorithm based on geometric optics to estimate the wavefront. The algorithm is relatively new and has not found application in operating adaptive optics systems. Further analysis of the noise propagation in the algorithm, sensor resolution, and precision is presented. We also made some observations on the implementation of the geometric wavefront sensor based on image recovery through projections.