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Proceedings Paper

Performance analysis of Kalman filter and minimum variance controllers for multi conjugate adaptive optics
Author(s): Piotr Piatrou; Michael Roggemann
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Paper Abstract

In the framework of zonal approach for Multi Conjugate Adaptive Optics (multiple-mirror, multiple-guide star) we investigate a predictive Kalman Filter (KF) based controller and a non-predictive classical Minimum Variance (MV) algorithm. The main goal of this work is to compare phase estimation performance achievable by the computationally more expensive Kalman filter approach, which explicitly accounts for the atmospheric turbulence temporal behavior through a first order autoregressive evolution model, and a simpler MV algorithm with and without temporal prediction. For representative examples of the Palomar 5.1 meter telescope single conjugate and Gemini-South 8 meter telescope multi conjugate adaptive optics systems the performance of KF and MV controllers has been compared with respect to their turbulence estimation capability. We have found that the KF algorithm, showing superior performance for single conjugate adaptive optics systems, is less effective in multi conjugate case. It has also been shown that MV algorithm with a temporal prediction added to it can work nearly as good as KF.

Paper Details

Date Published: 30 August 2005
PDF: 9 pages
Proc. SPIE 5894, Advanced Wavefront Control: Methods, Devices, and Applications III, 58940X (30 August 2005); doi: 10.1117/12.614570
Show Author Affiliations
Piotr Piatrou, Michigan Technological Univ. (United States)
Michael Roggemann, Michigan Technological Univ. (United States)

Published in SPIE Proceedings Vol. 5894:
Advanced Wavefront Control: Methods, Devices, and Applications III
Mark T. Gruneisen; John D. Gonglewski; Michael K. Giles, Editor(s)

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