Trajectory Optimization for Aircraft Swarms Strike Missions Based on Distributed Receding Horizon

To enhance the real-time trajectory planning capability of aircraft swarms in dynamic and antagonistic environments for cooperative saturation attacks, a decision-making approach integrating a multiphase pseudospectral method with receding horizon optimization is proposed. Firstly, a multi-objective optimization problem for cooperative strike missions of aircraft swarms is formulated based on the aircraft dynamics model, where the constraints such as performance limits, inter-swarm distance, and obstacle avoidance are considered, and the terms of target-approach, attack angle deviation minimization, and time synchronization are incorporated. Thereby a model of swarm trajectory optimization problem is established. Secondly, nonlinear constraints are systematically augmented into the objective function through exact penalty functions to further accelerate the solution process of the optimization problem. Finally, the multiphase pseudospectral method is employed in a receding horizon framework to iteratively solve the aforementioned swarm trajectory optimization problem. To validate the effectiveness of the proposed method, a scenario of aircraft swarm cooperatively striking dynamic targets is simulated. Numerical simulation results show that the aircraft swarm successfully avoids threat zones and achieves saturation strikes on dynamic targets. The proposed method features rapid computation speed (with an average optimization time of less than 0.5 s), demonstrating its capability for online trajectory optimization.