Multi-UAV collaborative trajectory planning for non-cooperative target tracking in complex environment

This paper proposes a novel collaborative trajectory planning method for non-cooperative target tracking using multiple UAVs in complex environment. To address complex multiple constraints and inherent nonlinearities, a nonlinear model predictive control (NMPC) modeling approach based on a fuzzy objective optimization framework and an improved grey wolf optimizer with efficient and stably (GWO-ES) solution method are presented. A motion model for non-cooperative ground target based on the current statistical model (CSM) is established, and extended kalman filter (EKF) is employed for state estimation and prediction. Subsequently, considering the intricacies of trajectory planning in complex environments and the nonlinearity of fixed-wing UAV dynamics, a fuzzy multi-objective optimization framework-based NMPC model is proposed, which takes into account objective optimization priority and satisfaction. Finally, based on the proposed framework, the satisfaction-based GWO-ES algorithm is proposed to efficiently and stably solve this complex, strongly nonlinear constrained model, enabling multiple UAVs to continuously track targets in complex environments with multiple tracking constraints. The simulation results indicate that, the GWO-ES algorithm demonstrates superior search capability and stability compared to other intelligent and mathematical methods, which can effectively meet the continuous tracking requirements of multiple UAVs for targets.