The pervasiveness of small Unmanned Aerial Vehicles (UAVs), due to low cost, ease of control, and portability, opens
the possibility of their use in urban environments for illegal or adversarial purposes. Such use includes unauthorized
surveillance, reconnaissance, and weaponization. Detecting adversarial UAVs in urban environments is difficult. Urban
canyons provide shielding from visibility. The small size of quadcopter-type UAVs limits the number of object pixels
available for processing, which reduces standoff detection performance. UAVs fly against a background of ground
motion clutter which can mask their motion. One possible solution to small UAV detection in urban environments uses
low-cost UAV surveillance platforms, equipped with optical sensors, together with computer vision algorithms to detect
adversarial UAVs in video data. In this paper we adapt the astronomical technique of transit photometry to detect small
UAVs, operating in urban environments, in video data. Transit photometry, typically used for exo-planet discovery,
detects small changes in background brightness due to a transiting object. As the UAV traverses across a bright
background region, for example, the vehicle occludes the background and reduces the perceived brightness. This
brightness dip may be used to infer the existence of a potential UAV passing across the background. The transit
photometry curve, resulting from this brightness dip, reveals information about the traversing vehicle. We investigate
mathematical properties of the transit photometry curve and derive a closed-form expression for it. We present numerical
results demonstrating the technique on real video data acquired from a small UAV operating in an urban environment.
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