Abstract

Drone inexpensive and operational flexibility contributed to its exponential increase by civil users, apart from military applications. This resulted in posing threats due to drone misuses, such as smuggling, unlawful imaging and other significant vulnerability that makes its detection necessary. The study demonstrated a theoretical model of extracting the m-Doppler signature due to rotating blades of a quadcopter drone, in forward scattering radar (FSR) geometry. The model was further validated experimentally by using a parabolic dish antenna in the receiver system of the FSR geometry. Before these, some reported efforts made to detect the drone by using different methodologies such as acoustic, video, audio-visual, radio frequency, radar systems and other non-technical approaches like netting were briefly presented. The result of the authors’ investigation revealed that the drone could be detected from the signature generated due to rotating blades based on the blade orientation. This signature can further be used to identify the drone from other flying targets existing within the same surveillance area.

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