An ADS-B Information-Based Collision Avoidance Methodology to UAV

Abstract

A collision avoidance method that is specifically tailored for UAVs (unmanned aerial vehicles) operating in converging airspace is proposed. The method is based on ADS-B messages and it aims to detect and resolve conflicts between UAVs. The proposed method involves two main steps. First, a UAV conflict-sensing scheme is developed, which utilizes ADS-B information flow path and analyzes the message format information. Second, an unscented Kalman filter is used to predict UAV trajectories based on the acquired ADS-B information. The predicted information is then used to determine potential conflict scenarios, and different deconfliction strategies are selected accordingly. These strategies include speed regulation, direction regulation, and compound deconfliction, and are mathematically validated using the velocity obstacle method. The feasibility and effectiveness of the proposed method are evaluated through simulation, and it is concluded that the method can significantly improve the conflict resolution capability of UAV flights. This research provides a valuable contribution to the field of UAV collision avoidance, and can serve as a theoretical foundation for further advancements in this area.