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