Drone cybersecurity issues, solutions, trend insights and future perspectives: a survey
This paper presented an exhaustive survey on the security and privacy issues of drones.
These security concerns were thoroughly dissected, particularly the aspect of cybersecurity …
These security concerns were thoroughly dissected, particularly the aspect of cybersecurity …
[HTML][HTML] Drone and controller detection and localization: Trends and challenges
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 …
unprecedented adoption in various application sectors due to their viability and low cost …
CNN-based single object detection and tracking in videos and its application to drone detection
DH Lee - Multimedia Tools and Applications, 2021 - Springer
This paper presents convolutional neural network (CNN)-based single object detection and
tracking algorithms. CNN-based object detection methods are directly applicable to static …
tracking algorithms. CNN-based object detection methods are directly applicable to static …
Detection of loaded and unloaded UAV using deep neural network
Unmanned aerial vehicles or drones quickly became cheaper, becoming more advanced
and affordable to the general public. And the ease of control made them popular among …
and affordable to the general public. And the ease of control made them popular among …
RF-based low-SNR classification of UAVs using convolutional neural networks
This paper investigates the problem of classification of unmanned aerial vehicles (UAVs)
from radio frequency (RF) fingerprints at the low signal-to-noise ratio (SNR) regime. We use …
from radio frequency (RF) fingerprints at the low signal-to-noise ratio (SNR) regime. We use …
Signal preprocessing technique with noise-tolerant for RF-based UAV signal classification
Since the beginning of the COVID-19 pandemic, the demand for unmanned aerial vehicles
(UAVs) has surged owing to an increasing requirement of remote, noncontact, and …
(UAVs) has surged owing to an increasing requirement of remote, noncontact, and …
RF detection and classification of unmanned aerial vehicles in environments with wireless interference
CJ Swinney, JC Woods - 2021 International Conference on …, 2021 - ieeexplore.ieee.org
Unmanned Aerial Vehicle (UAV) detection and classification methods include the use of
audio, video, thermal, RADAR and radio frequency (RF) signals. RF signals have the ability …
audio, video, thermal, RADAR and radio frequency (RF) signals. RF signals have the ability …
Decimeter-accuracy positioning for drones using two-stage trilateration in a GPS-denied environment
YE Chen, HH Liew, JC Chao… - IEEE Internet of Things …, 2022 - ieeexplore.ieee.org
This study proposes a high-accuracy two-stage trilateration method that enables real-time
positioning in global position system (GPS)-denied areas, such as unmanned aerial …
positioning in global position system (GPS)-denied areas, such as unmanned aerial …
[HTML][HTML] The effect of real-world interference on CNN feature extraction and machine learning classification of unmanned aerial systems
CJ Swinney, JC Woods - Aerospace, 2021 - mdpi.com
Small unmanned aerial systems (UASs) present many potential solutions and
enhancements to industry today but equally pose a significant security challenge. We only …
enhancements to industry today but equally pose a significant security challenge. We only …
A spatiotemporal neural network model for estimated-time-of-arrival prediction of flights in a terminal maneuvering area
Affected by the nondeterministic nature of flight trajectories, the external environment, and
airport operational conditions, the prediction of the estimated time of arrival (ETA) is one of …
airport operational conditions, the prediction of the estimated time of arrival (ETA) is one of …