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Vision algorithm for the Solar Aspect System of the HEROES mission

机译:HEROES任务的太阳视点系统的视觉算法

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This work covers the design and test of a machine vision algorithm for generating high-accuracy pitch and yaw pointing solutions relative to the sun for the High Energy Replicated Optics to Explore the Sun (HEROES) mission. It describes how images were constructed by focusing an image of the sun onto a plate printed with a pattern of small fiducial markers. Images of this plate were processed in real time to determine relative position of the balloon payload to the sun. The algorithm is broken into four problems: circle detection, fiducial detection, fiducial identification, and image registration. Circle detection is handled by an “Average Intersection” method, fiducial detection by a matched filter approach, identification with an ad-hoc method based on the spacing between fiducials, and image registration with a simple least squares fit. Performance is verified on a combination of artificially generated images, test data recorded on the ground, and images from the 2013 flight.
机译:这项工作涵盖了机器视觉算法的设计和测试,该算法可生成与太阳相关的高精度俯仰和偏航指向解决方案,以完成高能复制光学探索太阳(HEROES)任务。它描述了如何通过将太阳图像聚焦到印有小基准标记图案的板上来构造图像。对该板的图像进行实时处理,以确定气球有效载荷相对于太阳的相对位置。该算法分为四个问题:圆检测,基准检测,基准识别和图像配准。圆形检测通过“平均相交”方法,匹配过滤器方法进行基准检测,基于基准之间的间距采用即席方法进行识别以及通过简单的最小二乘拟合进行图像配准。结合人工生成的图像,记录在地面的测试数据以及2013年飞行的图像,对性能进行了验证。

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