Image Aided Relative Navigation for Air Vehicles Using a Passive, Statistical Predictive Rendering Approach

J. Michael Howard adn Michael J. Veth

Abstract:	Unmanned Aircraft Systems (UAS) have revolutionized the concept of military airpower [23]. They accomplish missions which are too dull, dirty, or dangerous to send a traditional piloted aircraft. As UAS have become larger, heavier, and weaponized their innate persistence has decreased. This new limitation to endurance motivated the need for an autonomous air refueling (AAR) capability for unmanned systems. This capability requires accurate, relative position information between an UAS and a refueling platform. A few current AAR systems rely on either GPS, which is subject to enemy influence and requires equipment modification to the refueling platform, or feature-based image analysis from on-board camera systems. Typical image aided position estimation techniques use trigonometry based on the image location of features, and are hindered by incorrectly identifying those features because of challenging aspect angles, lighting conditions, or feature occlusion. This often requires affixing unique, contrasting patterns to a refueling aircraft to increase accuracy. The research in this paper proposes a novel solution to the image aided, relative navigation AAR problem using a whole object, predictive rendering approach combined with an iterative search algorithm, tuned specifically for the AAR case. A 3D model of an object is rendered as an image or images and compared with images collected from a camera on-board the UAS. The system is capable of half meter accuracy at a range up to 40 meters, which is within the refueling envelope for the USAF boom-style refueling. The system accuracy improves as range decreases, and future research efforts could allow AAR without any modification to refueling platforms.
Published in:	Proceedings of the 24th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS 2011) September 20 - 23, 2011 Oregon Convention Center, Portland, Oregon Portland, OR
Pages:	3546 - 3556
Cite this article:	Veth, J. Michael Howard adn Michael J., "Image Aided Relative Navigation for Air Vehicles Using a Passive, Statistical Predictive Rendering Approach," Proceedings of the 24th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS 2011), Portland, OR, September 2011, pp. 3546-3556.
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