Image-based geolocalization for unmanned aerial vehicles (UAVs) Bildbasierte Geolokalisierung für UAVs

When unmanned aerial vehicles (UAVs) fly autonomous missions, they typically rely on global satellite navigation systems (GNSS) like GPS for global position estimation. However, GNSS signals can be easily jammed. We propose a camera-based method that uses onboard imagery and data from OpenStreetMap as a backup system for GNSS. First, the aerial imagery from the onboard camera is translated into a map-like representation. Then we match it with a reference map to infer the vehicle’s position. Experiments over a typically sized mission area are performed and exhibit localization accuracy close to 6 m. Our results show that the proposed method can serve as a backup to GNSS systems where suitable landmarks like buildings and roads are available.