Open AccessMicro‐Doppler signature for drone detection using FSR: a theoretical and experimental validation
Author(s) -
Musa Surajo Alhaji,
Raja Syamsul Azmir Raja Abdullah,
Sali Aduwati,
Ismail Alyani,
Abd Rashid Nur Emileen
Publication year - 2019
Publication title -
the journal of engineering
Language(s) - English
Resource type - Journals
ISSN - 2051-3305
DOI - 10.1049/joe.2019.0795
Subject(s) - drone , signature (topology) , computer science , quadcopter , artificial intelligence , radar , doppler effect , computer vision , real time computing , acoustics , remote sensing , aerospace engineering , engineering , telecommunications , physics , geography , mathematics , genetics , geometry , astronomy , biology
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.