Modeling astronomical adaptive optics performance with temporally filtered Wiener reconstruction of slope data

• Type: Article in International Scientific Journal
• Date: 2017

Authors

Correia, CM (Author) Other; Bond, CZ (Author) Other; Sauvage, JF (Author) Other; Fusco, T (Author) Other; Conan, R (Author) Other; Wizinowich, PL (Author) Other

Journal

Title: Journal of the Optical Society of America A: Optics and Image Science, and Vision

Vol. 34

Pages: 1877-1887

ISSN: 1084-7529

Publisher: Optical Society of America

Indexing

ISI Web of Knowledge - 21 Citations

Scopus - 28 Citations

Other information

Authenticus ID: P-014-ZC9

DOI: 10.1364/josaa.34.001877

Abstract (EN): We build on a long-standing tradition in astronomical adaptive optics (AO) of specifying performance metrics and error budgets using linear systems modeling in the spatial-frequency domain. Our goal is to provide a comprehensive tool for the calculation of error budgets in terms of residual temporally filtered phase power spectral densities and variances. In addition, the fast simulation of AO-corrected point spread functions (PSFs) provided by this method can be used as inputs for simulations of science observations with next-generation instruments and telescopes, in particular to predict post-coronagraphic contrast improvements for planet finder systems. We extend the previous results presented in Correia and Teixeira [J. Opt. Soc. Am. A 31, 2763 (2014)] to the closed-loop case with predictive controllers and generalize the analytical modeling of Rigaut et al. [Proc. SPIE 3353, 1038 (1998)], Flicker [Technical Report (W. M. Keck Observatory, 2007)], and Jolissaint [J. Eur. Opt. Soc. 5, 10055 (2010)]. We follow closely the developments of Ellerbroek [J. Opt. Soc. Am. A 22, 310 (2005)] and propose the synthesis of a distributed Kalman filter to mitigate both aniso-servo-lag and aliasing errors while minimizing the overall residual variance. We discuss applications to (i) analytic AO-corrected PSF modeling in the spatial-frequency domain, (ii) post-coronagraphic contrast enhancement, (iii) filter optimization for real-time wavefront reconstruction, and (iv) PSF reconstruction from system telemetry. Under perfect knowledge of wind velocities, we show that ~60 nm rms error reduction can be achieved with the distributed Kalman filter embodying antialiasing reconstructors on 10 m class high-order AO systems, leading to contrast improvement factors of up to three orders of magnitude at few ¿/D separations (~1 ¿ 5¿/D) for a 0 magnitude star and reaching close to one order of magnitude for a 12 magnitude star.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 11