Vector space approach for modelling a Hartmann wavefront sensor

The authors apply a vector space approach using matrix operations and linear algebra to develop a model of a Hartmann wavefront sensor. The wavefront sensor measures the records the wavefront phase over an aperture by dividing the total aperture in 69 subapertures. Wavefront sensor outputs obtained in experimental tests are analyzed to identify regions of linearity, nonlinearity, and saturation, and to estimate bias and noise. Since wavefront sensor measurements can be noise-corrupted, nonlinear, and limited in accuracy, a stochastic truth model that could be used to design an optimal controller to minimize the mean square phase front error is developed.<
>