High altitude UAV navigation using IMU, GPS and camera

This paper deals with the integration of measurements provided by inertial sensors (gyroscopes and accelerometers), GPS (Global Positioning System) and a video system in order to estimate position and attitude of an high altitude UAV (Unmanned Aerial Vehicle). In such a case, the vision algorithms present ambiguities due to the plane degeneracy. This ambiguity can be avoided fusing the video information with inertial sensors measurements. On the other hand, inertial sensors are widely used for aircraft navigation because they represent a low cost and compact solution, but their measurements suffer of several errors which cause a rapid divergence of position and attitude estimates. To avoid divergence, inertial sensors are usually coupled with other systems as for example GPS. A camera presents several advantages with respect to GPS as for example great accuracy and higher data rate. Moreover, it can be used in urban area or, more in general, where no useful GPS signal is present. On the contrary, it has lower data rate than inertial sensors and its measurements have latencies which can prejudice the performances and the effectiveness of the flight control system. The integration of inertial sensors with a camera allows exploiting the better features of both the systems, providing better performances in position and attitude estimation. The data fusion is performed via a multirate Unscented Kalman Filter (UKF) because of the nonlinear dynamic system equation. Experimental results show the effectiveness of the proposed method.