Attitude Estimation for a Fixed-Wing Aircraft Using Horizon Detection and Optical Flow

Abstract

We develop a method for estimating the flight critical parameters of pitch angle, roll angle and the three body rates using horizon detection and optical flow. We achieve this through the use of an image processing front-end to detect candidate horizon lines through the use of morphological image processing and the Hough transform. The optical flow of the image for each candidate line is calculated, and using these measurements, we are able to estimate the body rates of the aircraft. Using an Extended Kalman Filter (EFK), the candidate horizon lines are propagated and tracked through successive image frames, with statistically unlikely horizon candidates eliminated.

Results qualitativly describing the performance of the image processing front-end on real datasets are presented, followed by an analysis of the improvement when utilising the motion model of the vehicle.