As drone-based applications proliferate, paramount contactless sensing of airborne drones from the ground becomes indispensable. This work demonstrates concentrating on propeller rotational speed will substantially improve drone sensing performance and proposes an event-camera-based solution, \sysname. \sysname features two components: achieves accurate, real-time propeller speed estimation by mitigating ultra-high sensitivity of event cameras to environmental noise. leverages these speeds to infer both internal and external drone dynamics. Extensive evaluations in real-world drone delivery scenarios show that \sysname achieves a sensing latency of 3 and a rotational speed estimation error of merely 0.23%. Additionally, \sysname infers drone flight commands with 96.5% precision and improves drone tracking accuracy by over 22% when combined with other sensing modalities.

生成讲解博客的中文版本

生成AI智能校验的中文版本