Trajectory prediction for fighter aircraft ground collision avoidance based on the model predictive control technique

Abstract

Controlled flight into terrain accidents pose a significant threat to aviation safety, emphasizing the need for effective automatic ground collision avoidance system (Auto GCAS). However, the diversity and complexity of missions present considerable challenges to aircraft collision avoidance control. This paper proposes an approach for trajectory prediction based on the model predictive control (MPC) technique. Different from previous methods that rely on predefined fixed trajectories, the proposed approach incorporates constraints of aircraft state and actual terrain to generate an optimal trajectory. The safety and effectiveness of the method are demonstrated through integrating the trajectory prediction algorithm into the Auto GCAS system. The simulation results show that the MPC-based Auto GCAS can achieve optimal collision avoidance outcomes aligned with the aircraft's performance and mission needs.