Date of Award
Master of Science in Electrical Engineering
Department of Electrical and Computer Engineering
Scott L. Nykl, PhD.
Unmanned aerial vehicles (UAVs) increasingly require the capability to y autonomously in close formation including to facilitate automated aerial refueling (AAR). The availability of relative navigation measurements and navigation integrity are essential to autonomous relative navigation. Due to the potential non-availability of the global positioning system (GPS) during military operations, it is highly desirable that relative navigation can be accomplished without the use of GPS. This paper develops two algorithms designed to provide relative navigation measurements solely from a stereo image pair. These algorithms were developed and analyzed in the context of AAR using a stereo camera system modeling that of the KC-46. Algorithms were analyzed in simulation and then in flight test using two C-12C aircraft at the United States Air Force Test Pilot School. The first algorithm, the Vision and Bayesian Inference Based Integrity Monitor (V5), uses Bayesian inference and template matching to return a probability mass function (PMF) describing the position of an observed aircraft. This PMF provides a relative position estimate as well as a protection level--which characterizes the uncertainty of the relative position estimate--thus providing a degree of navigation integrity. Using both simulation and flight test data, mean V5 spherical error was less than one meter and protection levels reliably characterized algorithm uncertainty. The second algorithm, relative pose estimation with computer vision and iterative closest point (R7), uses stereo vision algorithms and the iterative closest point algorithm to return relative position and attitude estimates. Using both simulation and flight test data, mean R7 spherical error was less than 0.5 meters. Additionally, in flight test, mean R7 attitude errors were less than 3° in all axes.
DTIC Accession Number
Stuart, Thomas R., "Integrity Monitoring for Automated Aerial Refueling: A Stereo Vision Approach" (2018). Theses and Dissertations. 1825.