Detection, Identification and Tracking of UAVs and Drones
A special issue of Drones (ISSN 2504-446X). This special issue belongs to the section "Drone Design and Development".
Deadline for manuscript submissions: 24 April 2025 | Viewed by 5187
Special Issue Editors
Interests: mobile computing; wireless sensor networks; drone systems; operating systems; security
Interests: wireless sensor networks; drone systems; ubiquitous computing; health
Interests: mobile sensor networks; robot networks; networked embedded systems; mobile computing; wireless networks; embedded operating systems
Interests: internet of drones; design and implementation of unmanned aerial vehicles for aerial manipulation; sensing; recognition; and path planning for autonomous drone; machine learning and data analytics; SLAM algorithms and robotics control system
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The use of drones and UAVs has grown in importance for society in terms of sensing, monitoring, transport, and a variety of other key tasks and operations. The detection, identification, and tracking of such drones and UAVs have emerged as major needs as drones fly near airspaces where they may pose a collision threat to other aircraft, may compromise the security of a venue, or may violate the privacy of a domicile or event. The detection of drones, at both short and long ranges, is of significant interest, as is the remote recognition and identification of the model, type, and capabilities of such drones. The tracking of drones in the presence of other aerial distractions and interference is further emphasised. This Special Issue seeks to attract pioneering research that advances the topics of detection, identification, and tracking of drones and UAVs through novel algorithms, techniques, tools, systems, and applications. We expect that artificial intelligence (AI) and machine learning (ML) will play major roles in future generations of advances in these topics. We welcome work exploring new sensing modalities such as vision, radar, and lidar as well as sensor fusion techniques that may accelerate the localization of drones of tracking performance. We therefore invite submissions that can provide transformative new ideas on topics including, but not limited to, dramatic improvements of the accuracy, speed, robustness, security, privacy, affordability, and scalability of drone and UAV detection, identification, and tracking.
Prof. Dr. Richard Han
Dr. V.P Nguyen
Dr. Karthik Dantu
Dr. Endrowednes Kuantama
Guest Editors
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Drones is an international peer-reviewed open access monthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- detection
- tracking
- identification
- sensor fusion
- artificial intelligence
- machine learning
- localization
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