This paper presents a comprehensive review of current literature on drone detection and
classification using machine learning with different modalities. This research area has …

As the fastest growing segment of aviation, unmanned aerial systems (UAS) continue to
increase in number, technical complexity and capabilities. Numerous civilian and …

Usage of Unmanned Aerial Vehicles (UAVs) is growing rapidly in a wide range of consumer
applications, as they prove to be both autonomous and flexible in a variety of environments …

Thanks to recent technological advances, a new generation of low-cost, small, unmanned
aerial vehicles (UAVs) is available. Small UAVs, often called drones, are enabling …

This review explores radar‐based techniques currently utilised in the literature to monitor
small unmanned aerial vehicle (UAV) or drones; several challenges have arisen due to their …

The security threats caused by the popularity of Unmanned Aerial Vehicles (UAVs) have
received much attention. In this paper, a UAV detection and identification system based on …

Most of the investigations on the micro-Doppler (MD) effect caused by a small unmanned
aerial vehicle (UAV) have been conducted using joint time–frequency (JTF) images rather …

Deep neural networks (DNNs) have become a relevant subject in the classification of radio
frequency signals and remote sensing data. A primary challenge is a tradeoff between …

Protective measures against small unmanned aerial vehicles (UAVs) are vital from a
national security perspective. As a result, the importance of surveillance systems that …

Unmanned aerial vehicles (UAVs) have emerged as a rapidly growing technology seeing
unprecedented adoption in various application sectors due to their viability and low cost …