Deep learning for unmanned aerial vehicles detection: A review

N Al-lQubaydhi, A Alenezi, T Alanazi, A Senyor… - Computer Science …, 2024 - Elsevier
As a new type of aerial robotics, drones are easy to use and inexpensive, which has
facilitated their acquisition by individuals and organizations. This unequivocal and …

Radar target characterization and deep learning in radar automatic target recognition: A review

W Jiang, Y Wang, Y Li, Y Lin, W Shen - Remote Sensing, 2023 - mdpi.com
Radar automatic target recognition (RATR) technology is fundamental but complicated
system engineering that combines sensor, target, environment, and signal processing …

Deep reinforcement learning based resource allocation and trajectory planning in integrated sensing and communications UAV network

Y Qin, Z Zhang, X Li, W Huangfu… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
In this paper, multi-UAVs serve as mobile aerial ISAC platforms to sense and communicate
with on-ground target users. To optimize the communication and sensing performance, we …

Analysis of micro-Doppler signatures of small UAVs based on Doppler spectrum

KB Kang, JH Choi, BL Cho, JS Lee… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
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 …

UAV detection and localization based on multi-dimensional signal features

W Nie, ZC Han, Y Li, W He, LB Xie… - IEEE Sensors …, 2021 - ieeexplore.ieee.org
In recent years, unmanned aerial vehicles (UAVs) have received growing attention due to
security threats issues. Though UAV detection and positioning systems are commonly used …

Radar–communication integration for 6G massive IoT services

H Hong, J Zhao, T Hong, T Tang - IEEE Internet of Things …, 2021 - ieeexplore.ieee.org
The world is entering a new era with ubiquitous connectivity among billions of humans and
machines, ie, the sixth-generation (6G) massive Internet of Things (IoT). Radar and …

Drone and controller detection and localization: Trends and challenges

J Yousaf, H Zia, M Alhalabi, M Yaghi, T Basmaji… - Applied Sciences, 2022 - mdpi.com
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 …

RF-based low-SNR classification of UAVs using convolutional neural networks

E Ozturk, F Erden, I Guvenc - arXiv preprint arXiv:2009.05519, 2020 - arxiv.org
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 …

Complex sincnet for more interpretable radar based activity recognition

S Biswas, CO Ayna, SZ Gurbuz… - 2023 IEEE Radar …, 2023 - ieeexplore.ieee.org
Radio frequency (RF) sensing has been increasingly used in many applications such as fall-
motion recognition, human-machine interfacing, gesture controlled home appliances, and …

Boosting multi‐target recognition performance with multi‐input multi‐output radar‐based angular subspace projection and multi‐view deep neural network

E Kurtoğlu, S Biswas, AC Gurbuz… - IET Radar, Sonar & …, 2023 - Wiley Online Library
Current radio frequency (RF) classification techniques assume only one target in the field of
view. Multi‐target recognition is challenging because conventional radar signal processing …