Drone Detection

Drone detection research aims to develop robust and reliable systems for identifying and tracking unmanned aerial vehicles (UAVs), addressing security and safety concerns arising from their increasing prevalence. Current research focuses on improving detection accuracy and robustness in challenging conditions (low light, complex backgrounds, noise) using various sensor modalities (visual, infrared, RF, LiDAR) and advanced algorithms, including convolutional neural networks (CNNs), vision transformers (ViTs), and fusion techniques that combine multiple data sources. These advancements are significant for enhancing security in various sectors, from airspace management and critical infrastructure protection to wildlife monitoring and autonomous systems.