Advance and Refinement: The Evolution of UAV Detection and Classification Technologies
Vladislav Semenyuk, Ildar Kurmashev, Alberto Lupidi, Dmitriy Alyoshin,, Liliya Kurmasheva, Alessandro Cantelli-Forti

TL;DR
This review analyzes recent advancements in UAV detection and classification technologies, highlighting sensor fusion, AI, and machine learning innovations that improve accuracy, range, and system reliability from 2020 onward.
Contribution
It provides a comprehensive overview of recent detection methodologies, integrating AI and sensor fusion techniques, and predicts future technological developments in UAV detection systems.
Findings
Sensor fusion enhances detection accuracy and range.
AI and machine learning significantly improve system efficiency.
Technological innovations are expected to further boost UAV detection performance.
Abstract
This review provides a detailed analysis of the advancements in unmanned aerial vehicle (UAV) detection and classification systems from 2020 to today. It covers various detection methodologies such as radar, radio frequency, optical, and acoustic sensors, and emphasizes their integration via sophisticated sensor fusion techniques. The fundamental technologies driving UAV detection and classification are thoroughly examined, with a focus on their accuracy and range. Additionally, the paper discusses the latest innovations in artificial intelligence and machine learning, illustrating their impact on improving the accuracy and efficiency of these systems. The review concludes by predicting further technological developments in UAV detection, which are expected to enhance both performance and reliability.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsInfrared Target Detection Methodologies · Advanced Measurement and Detection Methods
MethodsFocus
