Chebychev moments based Drone Classification, Recognition and Fingerprinting

This paper introduces the use of a Chebychev moments' based feature for micro-Doppler based Classification, Recognition and Fingerprinting of Drones. This specific feature has been selected for its low computational cost and orthogonality property. The capability of the proposed feature extraction framework is assessed at three different levels...

Use of Symmetrical Peak Extraction in Drone Micro-Doppler Classification for Staring Radar

The commercialization of drones has granted the public with unprecedented access to unmanned aviation. As such, the detection, tracking, and classification of drones in radars have become an area in high demand to mitigate accidental or voluntary misuse of these platforms. This paper focuses on the classification of drone targets in a safety...

Radar Micro-Doppler Patterns for Drone's Characterisation

Micro-Doppler patterns of multi-propeller drones measured by radar systems are widely used in the classification of different drones, since the micro-Doppler patterns illustrate the velocity and motion properties of the drones. However, on this topic, there are a few issues the current researches have not tackled yet, and these will be discussed...

Simulation of Radar Micro-Doppler Patterns for Multi-Propeller Drones

This paper presents a thin-wire electromagnetic (EM) model of multi-propeller drone that generates drone micro-Doppler pattern efficiently as a function of radar parameters and propeller properties. Experimental results of propeller micro-Doppler pattern measured in anechoic chamber was investigated and used to validate the results produced...