Modeling astronomical adaptive optics performance with temporally filtered Wiener reconstruction of slope data.
Modeling astronomical adaptive optics performance with temporally filtered Wiener reconstruction of slope data.
复制标题
使用斜率数据的时间滤波维纳重建来建模天文自适应光学性能。
DOI：
--
复制
发表时间：
2017
影响因子：
1.9
通讯作者：
P. Wizinowich
中科院分区：
文献类型：
--
作者：
C. Correia;C. Bond;J. Sauvage;T. Fusco;R. Conan;P. Wizinowich
我们建立在天文自适应光学（AO）的一个长期的传统，在空间频率域中使用线性系统建模指定的性能指标和误差预算。我们的目标是提供一个全面的工具来计算误差预算的残留时间滤波相位功率谱密度和方差。此外，该方法提供的AO校正点扩散函数（PSF）的快速模拟可用作下一代仪器和望远镜科学观测模拟的输入，特别是预测行星发现系统的日冕对比度改善。我们推广了Correia和特谢拉[J. Opt. Soc. Am. A31，2763（2014）JOAOD 60740 -323210.1364/JOSAA.31.002763]的分析模型推广到具有预测控制器的闭环情况，并推广Rigaut等人的分析模型。[Proc.SPIE3353，1038（1998）PSISDG 0277 -786X10.1117/12.321649]，闪烁[技术报告（W. M. Keck Observatory，2007）]和Jolissaint [J. Eur. 5，10055（2010）1990-257310.2971/jeos.2010.10055]。我们密切关注Ellerbroek [J. Opt. Soc. Am. A22，310（2005）JOAOD 60740 -323210.1364/JOSAA.22.000310]，并提出了分布式卡尔曼滤波器的合成，以减轻非等-伺服-滞后和混叠误差，同时最小化总体残差方差。我们讨论的应用程序（一）分析AO校正PSF建模的空间频率域，（二）后coronagraphic对比度增强，（三）实时波前重建的滤波器优化，和（四）PSF重建系统遥测。在完全了解风速的情况下，我们证明了在10 m级高阶AO系统上采用分布式卡尔曼滤波器实现抗混叠重构，可以实现60 nm均方根误差的减小，对于0等星星，在几个λ/D间隔（λ 1-5λ/D）下，对比度改善因子高达3个数量级，对于12等星星，对比度改善因子接近1个数量级。
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. A31, 2763 (2014)JOAOD60740-323210.1364/JOSAA.31.002763] to the closed-loop case with predictive controllers and generalize the analytical modeling of Rigaut et al. [Proc. SPIE3353, 1038 (1998)PSISDG0277-786X10.1117/12.321649], Flicker [Technical Report (W. M. Keck Observatory, 2007)], and Jolissaint [J. Eur. Opt. Soc.5, 10055 (2010)1990-257310.2971/jeos.2010.10055]. We follow closely the developments of Ellerbroek [J. Opt. Soc. Am. A22, 310 (2005)JOAOD60740-323210.1364/JOSAA.22.000310] 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 λ/D separations (∼1-5λ/D) for a 0 magnitude star and reaching close to one order of magnitude for a 12 magnitude star.