Vision-based navigation for unmanned aircraft using ground feature points and terrain elevation data

A vision-based navigation approach using digital terrain elevation data and a monocular camera is addressed for autonomous navigation of unmanned aircraft. Previous vision-based terrain-referenced navigation algorithms use visual measurements to update vehicle position. This study expands the use of the visual measurements and the terrain data by designing the navigation filter to update 3-axis attitude and velocity as well as position. An observation model for updating position and attitude compares height estimates of ground features, computed from the visual measurements, with terrain elevation data. Additionally, the eight-point algorithm is adopted to extract direction of camera movement to update velocity in the navigation filter. A simulation study is conducted to verify the feasibility of the proposed method and the effect of visual measurement errors.