title: Nonstationary multiscale turbulence simulation based on local PCA.
abstract: Turbulence simulation methods are of fundamental importance for evaluating the performance of control strategies for Adaptive Optics (AO) systems. In order to obtain a reliable evaluation of the performance a statistically accurate turbulence simulation method has to be used. This work generalizes a previously proposed method for turbulence simulation based on the use of a multiscale stochastic model. The main contributions of this work are: first, a multiresolution local PCA representation is considered. In typical operating conditions, the computational load for turbulence simulation is reduced approximately by a factor of 4, with respect to the previously proposed method, by means of this PCA representation. Second, thanks to a different low resolution method, based on a moving average model, the wind velocity can be in any direction (not necessarily that of the spatial axes). Finally, this paper extends the simulation procedure to generate, if needed, turbulence samples by using a more general model than that of the frozen flow hypothesis.
authors.affiliation: Department of Information Engineering, University of Padova, via Gradenigo 6/B, 35131 Padova, Italy. Electronic address: beghi@dei.unipd.it.
authors.forename: Alessandro
authors.initials: A
authors.lastname: Beghi
authors.affiliation: Department of Information Engineering, University of Padova, via Gradenigo 6/B, 35131 Padova, Italy. Electronic address: angelo.cenedese@unipd.it.
authors.forename: Angelo
authors.initials: A
authors.lastname: Cenedese
authors.affiliation: Interdepartmental Research Center of Geomatics, University of Padova, via dell'Università 16, 35020 Legnaro, PD, Italy. Electronic address: masiero@dei.unipd.it.
authors.forename: Andrea
authors.initials: A
authors.lastname: Masiero
keywords: Adaptive optics; Fast Fourier transforms; Multiscale stochastic systems; Principal component analysis; Signal processing