LiDAR Technology for UAV Detection: From Fundamentals and Operational Principles to Advanced Detection and Classification Techniques
Seidaliyeva U. Ilipbayeva L. Utebayeva D. Smailov N. Matson E.T. Tashtay Y. Turumbetov M. Sabibolda A.
May 2025Multidisciplinary Digital Publishing Institute (MDPI)
Sensors
2025#25Issue 9
As unmanned aerial vehicles (UAVs) are increasingly employed across various industries, the demand for robust and accurate detection has become crucial. Light detection and ranging (LiDAR) has developed as a vital sensor technology due to its ability to provide rich 3D spatial information, particularly in applications such as security and airspace monitoring. This review systematically explores recent innovations in LiDAR-based drone detection, deeply focusing on the principles and components of LiDAR sensors, their classifications based on different parameters and scanning mechanisms, and the approaches for processing LiDAR data. The review briefly compares recent research works in LiDAR-based only and its fusion with other sensor modalities, the real-world applications of LiDAR with deep learning, as well as the major challenges in sensor fusion-based UAV detection.
3D object detection , deep learning , deep learning for point cloud processing , drone detection , LiDAR , LiDAR classifications , object detection , point clouds , scanning mechanism , UAV detection , unmanned aerial vehicles (UAVs)
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Metropolitan College (MET), Boston University, Boston, 02215, MA, United States
Department of Radio Engineering, Electronics and Telecommunications, International IT University, Almaty, 050040, Kazakhstan
Department of Computer Science, SDU University, Almaty, 040900, Kazakhstan
Department of Electronics, Telecommunications and Space Technologies, Satbayev University, Almaty, 050013, Kazakhstan
Department of Mechanical Engineering and Robotics, U. A. Joldasbekov Institute of Mechanics and Engineering, Almaty, 050010, Kazakhstan
Department of Computer and Information Technology, Purdue University, West Lafayette, 47907-2021, IN, United States
Metropolitan College (MET)
Department of Radio Engineering
Department of Computer Science
Department of Electronics
Department of Mechanical Engineering and Robotics
Department of Computer and Information Technology
10 лет помогаем публиковать статьи Международный издатель
Книга Публикация научной статьи Волощук 2026 Book Publication of a scientific article 2026