Suppr超能文献

使用SPGD算法在光学合成孔径成像中基于场景的共相的实验演示。

Experimental demonstration of scene-based cophasing in optical synthetic aperture imaging using the SPGD algorithm.

作者信息

Hirose Makoto, Miyamura Norihide

出版信息

Appl Opt. 2024 May 20;63(15):4157-4164. doi: 10.1364/AO.522829.

Abstract

Large-aperture telescopes based on optical synthetic aperture imaging are investigated for recent high-resolution spaceborne observations. An enabling technique of aperture synthesis is a cophasing method to suppress a piston-tip-tilt error between sub-apertures. This paper proposes a scene-based cophasing technique using the stochastic parallel gradient descent (SPGD) algorithm, assuming application to high-resolution Earth observation. A significant advantage of the SPGD algorithm is a model-less cophasing capability based on extended scenes, but the simultaneous scene-based piston-tip-tilt correction between multiple apertures has not been demonstrated. In this paper, we developed a tabletop synthetic aperture imaging system with 37 sub-apertures and demonstrated extended-scene-based piston-tip-tilt control by optimizing applied voltages to 111 actuators simultaneously. The demonstration experiments used not only static scenes but also a time-varying dynamic scene for observation targets. In every measurement, the proposed scene-based approach reduced the initially defined piston-tip-tilt errors, and the image sharpness significantly improved, although the correction rate in the dynamic scene observation was slower. Finally, this paper discusses the influence of scene dynamics on image-based cophasing.

摘要

针对近期的高分辨率星载观测,对基于光学合成孔径成像的大口径望远镜展开了研究。孔径合成的一项关键技术是共相方法,用于抑制子孔径之间的活塞-倾斜误差。本文提出了一种基于场景的共相技术,采用随机并行梯度下降(SPGD)算法,并假设其应用于高分辨率地球观测。SPGD算法的一个显著优势是基于扩展场景的无模型共相能力,但多个孔径之间基于场景的活塞-倾斜同步校正尚未得到验证。在本文中,我们开发了一个具有37个子孔径的桌面合成孔径成像系统,并通过同时优化施加在111个致动器上的电压,展示了基于扩展场景的活塞-倾斜控制。演示实验不仅使用了静态场景,还使用了随时间变化的动态场景作为观测目标。在每次测量中,尽管动态场景观测中的校正速率较慢,但所提出的基于场景的方法减少了最初定义的活塞-倾斜误差,图像清晰度显著提高。最后,本文讨论了场景动态对基于图像的共相的影响。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验