Proceedings of the International Conference on Advancements in Computing Technologies and Artificial Intelligence (COMPUTATIA-2025)

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UAV Detection and Identification: A Comparative Review of Current Methods and Future Directions

Authors
Bharti Sharma1, *, Amol Purohit1
1Department of Computer Science and Engineering, Vivekananda Global University, Jaipur, India
*Corresponding author. Email: bhartisharmavit@gmail.com
Corresponding Author
Bharti Sharma
Available Online 19 April 2025.
DOI
10.2991/978-94-6463-700-7_17How to use a DOI?
Keywords
Audio Sensing; RF Fingerprint; Radar Sensing; Visual Sensing; Unmanned Aerial Vehicles (UAVs); UAV Detection; UAV Identification
Abstract

Unmanned aerial vehicles (UAVs), also known as flying robots or drones, were used exclusively for military purposes only in the early 1990s. Now drones are easy to use and inexpensive; therefore, they are easily accessible by individuals as well as organizations. The rapid development of UAVs provides facilities in various sectors, including agriculture, delivery, surveillance, videography, photography, rescue and search operations, and more. Indeed, the expanded use of UAVs contributes to various technical, security, and public safety challenges and has intensified the need for advanced UAV detection and identification systems. This review explores the latest techniques for detecting and identifying drones, focusing on new strategies to tackle the growing concerns around UAVs. We categorize and examine various detection methods, like radar sensing, radio frequency (RF) sensing, sound-based, and vision-based techniques, noting their benefits and drawbacks. Furthermore, this review highlights the importance of other methods, like RF fingerprinting, to improve the precision and efficiency of UAV detection and identification systems, thus increasing security against potential UAV threats.

Copyright
© 2025 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the International Conference on Advancements in Computing Technologies and Artificial Intelligence (COMPUTATIA-2025)
Series
Advances in Intelligent Systems Research
Publication Date
19 April 2025
ISBN
978-94-6463-700-7
ISSN
1951-6851
DOI
10.2991/978-94-6463-700-7_17How to use a DOI?
Copyright
© 2025 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Bharti Sharma
AU  - Amol Purohit
PY  - 2025
DA  - 2025/04/19
TI  - UAV Detection and Identification: A Comparative Review of Current Methods and Future Directions
BT  - Proceedings of the International Conference on Advancements in Computing Technologies and Artificial Intelligence (COMPUTATIA-2025)
PB  - Atlantis Press
SP  - 205
EP  - 217
SN  - 1951-6851
UR  - https://doi.org/10.2991/978-94-6463-700-7_17
DO  - 10.2991/978-94-6463-700-7_17
ID  - Sharma2025
ER  -