This study introduces a unified control framework for fixed-wing unmanned aerial vehicles (UAVs) equipped with a pan-tilt (PT) camera, aimed at performing an end-to-end mission from initial target detection to precise terminal engagement. The proposed system employs a three-phase strategy: a vision-based target acquisition phase, an NMPC-based tracking phase, and a terminal guidance phase.
During the tracking phase, the framework utilizes an Unscented Kalman Filter (UKF) to fuse YOLO-based visual detections with inertial measurements, enabling robust target state estimation under unknown dynamics. To ensure reliable visual contact, we introduce a constraint-aware Nonlinear Model Predictive Control (NMPC) strategy that incorporates Control Barrier Functions (CBFs) to explicitly prevent UAV self-occlusion, a common limitation in fixed-wing tracking.
Upon satisfying terminal engagement conditions, the system seamlessly transitions control to a quaternion-based Biased Proportional Navigation Guidance (BPNG) law, enforcing precise impact angle constraints. High-fidelity simulations demonstrate that the framework achieves stable, robust tracking and accurate terminal interception while strictly respecting the vehicle's dynamic limits and camera field-of-view constraints.
Blogger's Review: This paper presents an effective control framework that addresses the challenges of target tracking and engagement for fixed-wing UAVs in dynamic environments, particularly the issue of self-occlusion, indicating significant practical applications.