Vision-aided Navigation for Autonomous Aircraft Based on Unscented Kalman Filter

Abstract

A vision-aided navigation system for autonomous aircraft is described in this paper. The vision navigation of the aircraft to the known scence is performed with a camera fixed on the aircraft. The location and pose of the aircraft are estimated with the corresponding control points which can be detected in the images captured. The control points are selected according their saliency and are tracked in sequential images based on Fourier-Melline transform. The simulation model of the aircraft dynamics and vision-aided navigation system based on Matlab/Simulink is built.The unscented Kalman filter is used to fuse the aircraft state information provided by the vision system and the inertial navigation system. Simulation results show that the vision-based navigation system provides satisfactory results of both accuracy and reliability.

DOI: http://dx.doi.org/10.11591/telkomnika.v11i2.2250