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Localization of low-cost Unmanned Aerial Vehicles (UAVs) often relies onGlobal Navigation Satellite Systems (GNSS). GNSS are susceptible to bothnatural disruptions to radio signal and intentional jamming and spoofing by anadversary. A typical way to provide georeferenced localization without GNSS forsmall UAVs is to have a downward-facing camera and match camera images to amap. The downward-facing camera adds cost, size, and weight to the UAV platformand the orientation limits its usability for other purposes. In this work, wepropose a Monte-Carlo localization method for georeferenced localization of anUAV requiring no infrastructure using only inertial measurements, a camerafacing an arbitrary direction, and an orthoimage map. We performorthorectification of the UAV image, relying on a local planarity assumption ofthe environment, relaxing the requirement of downward-pointing camera. Wepropose a measure of goodness for the matching score of an orthorectified UAVimage and a map. We demonstrate that the system is able to localize globally anUAV with modest requirements for initialization and map resolution.

GNSS-denied geolocalization of UAVs by visual matching of onboard camera images with orthophotos