Algorithm for the Solar Aspect System of the High Energy Replicated

Title of Document: VISION ALGORITHM FOR THE SOLAR ASPECT SYSTEM OF THE HIGH ENERGY REPLICATED OPTICS TO EXPLORE THE SUN MISSION Alexander Krishnan Cramer, M.S., 2014 Directed By: Professor Ramalingam Chellappa, Department of Electrical and Computer Engineering This work covers the design and test of a machine vision algorithm for generating highaccuracy pitch and yaw pointing solutions relative to the sun on a high altitude balloon. It describes how images were constructed by focusing an image of the sun onto a plate printed with a pattern of small cross-shaped fiducial markers. Images of this plate taken with an off-the-shelf camera were processed 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, and identification with an ad-hoc method based on the spacing between fiducials. Performance is verified on real test data where possible, but otherwise uses artificially generated data. Pointing knowledge is ultimately verified to meet the 20 arcsecond requirement. VISION ALGORITHM FOR THE SOLAR ASPECT SYSTEM OF THE HIGH ENERGY REPLICATED OPTICS TO EXPLORE THE SUN MISSION