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高对比度成像波前检测及校正算法研究

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空间超高对比度成像技术是开展类地行星直接成像探测的必要条件,该技术的实现依赖于空间星冕仪系统对光学波前的精确控制,因此需要发展专用的在轨波前检测及校正算法.此类算法已在地基自适应光学系统中广泛应用,但在空间中,受限于航天用CPU性能和选型限制,无法基于纯CPU运算设计.本文基于FPGA和CPU混合架构实现波前校正,在兼顾硬件资源和运算精度的条件下,能够锁定系外行星探测所需的高对比度成像暗区.上述混合架构的算法在大规模自适应光学系统中也具有显著的速度优势,针对100 × 100子孔径数的自适应光学系统,波前处理延时缩短1281.826 μs,可满足为地基大口径望远镜配备的ExAO、GLAO和MCAO等自适应光学系统高速并行计算的需求.
Research on wavefront detection and correction algorithms for high-contrast imaging
Ultra-high contrast imaging in space is essential for the direct imaging detection of Earth-like planets,the a-chievement of which depends on the precise control of the optical wavefront by the space coronagraph system,and there-fore requires the development of specialized on-orbit algorithms dedicated to wavefront detection and correction.While such algorithms have been widely used in ground-based adaptive optics systems,but in space,they cannot be designed based on pure CPU computing due to the limitations of space CPU performance and selection.Based on the hybrid archi-tecture of FPGA and CPU,the wavefront correction is realized,which is capable of locking the high-contrast imaging dark region required for exoplanet detection while taking into account the hardware resources and computing accura-cy.The algorithm of the above hybrid architecture also has a significant speed advantage in large-scale adaptive optics systems,and the wavefront processing delay is shortened by 1281.826 μs for a 100 × 100 sub-aperture adaptive optics system,which can meet the demand for high-speed parallel computation of the adaptive optics systems,such as the Ex-AO,the GLAO,and the MCAO,which are equipped with the ground-based large-aperture telescopes.

adaptive opticshigh-contrast imagingwavefront detection and correctionFPGA

陈曌瑜、张熙、王钢

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中国科学院南京天文光学技术研究所,江苏南京 210042

中国科学院天文光学技术重点实验室(南京天文光学技术研究所),江苏南京 210042

中国科学院大学,北京 100049

自适应光学 高对比度成像 波前检测及校正 FPGA

2024

激光与红外
华北光电技术研究所

激光与红外

CSTPCD北大核心
影响因子:0.723
ISSN:1001-5078
年,卷(期):2024.54(12)