Advances in UAV Detection, Classification and Tracking
Wang, Daobo (editor)
Ali, Zain Anwar (editor)
"Advances in UAV Detection, Classification and Tracking" is a comprehensive book that explores the latest techniques and advancements in unmanned aerial vehicle (UAV) detection, classification, and tracking. As UAV technology continues to evolve and become more accessible, there is a growing need for effective methods to detect, identify, and track these devices in various scenarios. This reprint provides a thorough overview of the state-of-the-art approaches for UAV detection, classification, and tracking, covering both theoretical and practical aspects.The reprint begins by introducing the basics of UAVs and their various applications, followed by a detailed overview of the challenges associated with UAV detection, classification, and tracking. The authors then present the latest techniques and algorithms used in the field, including machine-learning-based approaches, computer vision techniques, and sensor fusion techniques. The reprint also covers the challenges of real-world applications, such as dealing with occlusions, sensor noise, and environmental factors.With contributions from leading experts in the field, "Advances in UAV Detection, Classification and Tracking" is an essential resource for researchers, engineers, and practitioners working on UAV detection, classification, and tracking. It is also a valuable reference for graduate students and anyone interested in the latest advancements in this rapidly evolving field.
Keywordsdistributed electric propulsion; coordinated thrust control; fault-tolerant control; flight simulation; autonomous navigation; gimbal design; obstacle avoidance; target tracking; unmanned aerial vehicles; law enforcement; tiltrotor; blade element theory; flight mechanical model; stability analysis; social learning; ant colony optimization; multi-agent system; visual tracking system; embedded system; drone; omnidirectional mobile robot; multi-target association; topological sequences; triangular networks; global consistency; similar transformation invariance; micro-Doppler; radar; target; classification; unmanned aerial vehicle; motion planning; optimization techniques; attention mechanism; anti-occlusion; location prediction; convolutional neural network CNN; YOLO deep learning; UAV; drone detection; drone recognition; automatic target recognition (ATR); classify while scan (CWS); drone detection radar; detection response time (DRT); unmanned air traffic management (UTM); object detection; deep learning; adaptive cluster; cognitive micro-Doppler radar; Doppler resolution; JEM signals; radar dwell time; advancement; tracking and communication threats; three-dimensional circumnavigation control; elliptical multi-orbit; UAV group; small-object detection; backbone design; object positioning; object classification; UAV flight experiment; astronaut detection; astronaut accompanying; intravehicular visual navigation; semi-structured environment; dynamic scenes; n/a
Webshop linkhttps://mdpi.com/books/pdfview ...
Publication date and placeBasel, 2023
Technology: general issues
History of engineering & technology
Energy industries & utilities