Welcome to the new version of CaltechAUTHORS. Login is currently restricted to library staff. If you notice any issues, please email coda@library.caltech.edu
Published February 7, 2003 | Published
Book Section - Chapter Open

Sparse-matrix wavefront reconstruction: simulations and experiments

Abstract

Adaptive optics systems with Shack-Hartmann wavefront sensors require reconstruction of the atmospheric phase error from subaperture slope measurements, with every sensor in the array being used in the computation of each actuator command. This fully populated reconstruction matrix can result in a significant computational burden for adaptive optics systems with large numbers of actuators. A method for generating sparse wavefront reconstruction matrices for adaptive optics is proposed. The method exploits the relevance of nearby subaperture slope measurements for control of an individual actuator, and relies upon the limited extent of the influence function for a zonal deformable mirror. Relying only on nearby sensor information can significantly reduce the calculation time for wavefront reconstruction. In addition, a hierarchic controller is proposed to recover some of the global wavefront information. The performance of these sparse wavefront reconstruction matrices was evaluated in simulation, and tested on the Palomar Adaptive Optics System. This paper presents some initial results from the simulations and experiments.

Additional Information

© 2003 Society of Photo-Optical Instrumentation Engineers (SPIE). This work was performed in part at the Jet Propulsion Laboratory, California Institute of Technology, under contract with the National Aeronautics and Space Administration. Observations at the Palomar Observatory were made as part of a continuing collaborative agreement between Palomar Observatory and the Jet Propulsion Laboratory.

Attached Files

Published - 1035.pdf

Files

1035.pdf
Files (286.4 kB)
Name Size Download all
md5:d8bff5a3dcfada5173ec65b24ae76cac
286.4 kB Preview Download

Additional details

Created:
August 19, 2023
Modified:
January 14, 2024