Kalman filtering to suppress spurious signals in Adaptive Optics control Page: 4 of 54
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In many scenarios, an Adaptive Optics (AO) control system operates in
the presence of temporally non-white noise. We use a Kalman filter with a
state space formulation that allows suppression of this colored noise, hence
improving residual error over the case where the noise is assumed to be
white. We demonstrate the effectiveness of this new filter in the case of the
estimated Gemini Planet Imager tip-tilt environment, where there are both
common-path and non-common path vibrations. We discuss how this same
framework can also be used to suppress spatial aliasing during predictive
wavefront control assuming frozen flow in a low-order AO system without a
spatially filtered wavefront sensor, and present experimental measurements
from Altair that clearly reveal these aliased components. 2010 Optical
Society of America
OCIS codes: 010.1080, 010.1285
Significant advances have been made in applying advanced control systems techniques
to Adaptive Optics (AO) wavefront control. Most of these techniques are founded in
the Kalman filter and, more broadly, the linear quadratic gaussian (LQG) formalisms
and are as such model-based. Important advances in this area include the general
closed-loop Kalman filtering approach of Le Roux et al  and Poyneer et al's Predic-
tive Fourier Control (PFC) , which uses the Kalman framework to independently
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Poyneer, L & Veran, J P. Kalman filtering to suppress spurious signals in Adaptive Optics control, article, March 29, 2010; Livermore, California. (digital.library.unt.edu/ark:/67531/metadc835045/m1/4/: accessed May 28, 2018), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.