Non-linear wavefront reconstruction methods for pyramid sensors using Landweber and Landweber-Kaczmarz iteration
arXiv:1808.07673 · doi:10.1364/AO.57.008790
Abstract
Accurate and robust wavefront reconstruction methods for pyramid wavefront sensors are in high demand as these sensors are planned to be part of many instruments currently under development for ground based telescopes. The pyramid sensor relates the incoming wavefront and its measurements in a non-linear way. Nevertheless, almost all existing reconstruction algorithms are based on a linearization of the model. The assumption of a linear pyramid sensor response is justifiable in closed loop AO when the measured phase information is small but may not be reasonable in reality due to unpreventable errors depending on the system such as non common path aberrations. In order to solve the non-linear inverse problem of wavefront reconstruction from pyramid sensor data we introduce two new methods based on the non-linear Landweber and Landweber-Kaczmarz iteration. Using these algorithms we experience high-quality wavefront estimation especially for the non-modulated sensor by still keeping the numerical effort feasible for large-scale AO systems.
References in corpus (4)
- Large Binocular Telescope Adaptive Optics System: New achievements and perspectives in adaptive optics
- General formalism for Fourier based Wave Front Sensing
- Efficient, Nonlinear Phase Estimation with the Non-Modulated Pyramid Wavefront Sensor
- High Contrast Imaging in the Visible: First Experimental Results at the Large Binocular Telescope
Cited by in corpus (6)
- Nonlinear wavefront reconstruction with convolutional neural networks for Fourier-based wavefront sensors
- Real-time Adaptive Optics with pyramid wavefront sensors: A theoretical analysis of the pyramid sensor model
- Non-modulated pyramid wavefront sensor: Use in sensing and correcting atmospheric turbulence
- Real-time Adaptive Optics with pyramid wavefront sensors: Accurate wavefront reconstruction using iterative methods
- Deep learning estimation of complex reverberant wave fields by a programmable metasurface
- A 5kHz modulator for pyramid wavefront sensors