International Journal of Robotics Research
Horizon Profile Detection for Attitude Determination
Journal of Intelligent and Robotic Systems
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A method has been developed for estimating pitch angle, roll angle, and aircraft body rates based on horizon detection and temporal tracking using a forward-looking camera, without assistance from other sensors. Using an image processing front end, we select several lines in an image that may or may not correspond to the true horizon. The optical flow at each candidate line is calculated, which may be used to measure the body rates of the aircraft. Using an extended Kalman filter (EKF), the aircraft state is propagated using a motion model and a candidate horizon line is associated using a statistical test based on the optical flow measurements and the location of the horizon. Once associated, the selected horizon line, along with the associated optical flow, is used as a measurement to the EKF. To test the accuracy of the algorithm, two flights were conducted, one using a highly dynamic uninhabited airborne vehicle (UAV) in clear flight conditions and the other in a human-piloted Cessna 172 in conditions in which the horizon was partially obscured by terrain, haze, and smoke. The UAV flight resulted in pitch and roll error standard deviations of 0.42 and 0.71 deg, respectively, when compared with a truth attitude source. The Cessna flight resulted in pitch and roll error standard deviations of 1.79 and 1.75 deg, respectively. The benefits of selecting and tracking the horizon using a motion model and optical flow rather than naively relying on the image processing front end are demonstrated. © 2011 Wiley Periodicals, Inc. © 2011 Wiley Periodicals, Inc.