Unmanned Aerial Vehicles (UAVs) have experienced remarkable progress and widespread utilization, highlighting the need for robust detection and classification systems to ensure safety and security. This paper presents a comprehensive study on UAV and payload detection and classification, emphasizing the fusion of multiple data sources to enhance accuracy and reliability. A fusion system integrating radar and Pan-Tilt-Zoom (PTZ) camera data is developed and evaluated. Experimental results demonstrate the effectiveness of the proposed approach, achieving a classification accuracy of > 94% for UAV detection and > 90% for payload classification. The findings underscore the system's potential for real-world applications in UAV and payload detection and classification scenarios, addressing the growing demands in this field.
Real-Time UAV and Payload Detection and Classification System Using Radar and Camera Sensor Fusion
2023-10-01
4967868 byte
Conference paper
Electronic Resource
English
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