A Unified and Persistent Interception Control of Multicopters With Strapdown Monocular Camera

The proliferation of unauthorized drones poses severe threats to low-altitude security, highlighting the critical need for robust autonomous interception systems. To address this challenge, this article proposes a persistent interception estimation framework. By leveraging a spherical imaging model and incorporating it into a Monte Carlo localization (MCL) approach, this framework precisely estimates the relative bearing between the interceptor and the target even when the target exits the field of view, thereby endowing the interception system with persistent pursuit capabilities. Furthermore, we develop a unified image-based visual servo (IBVS) control scheme applicable for both initial and subsequent interception phases. The effectiveness of our persistent interception system, integrating the estimation framework with the control scheme, is rigorously validated through hardware-in-the-loop (HIL) simulations and real-world flight experiments. Results demonstrate significant improvements in interception success rates compared to single-attempt interception methods and state-of-the-art SE(3)-EKF approaches during temporary vision loss scenarios. These results indicate a significant advancement in autonomous multicopter interception for antidrone applications.