Two-stage cooperative trajectory planning for hypersonic glide vehicles: A bio-inspired optimization approach

In the cooperative guidance of multiple hypersonic glide vehicles (HGVs) during the terminal dive phase, existing approaches seldom analyze the strict temporal simultaneity of phase entry, especially across the glide-to-dive transition. This paper focuses on the transition challenges across the glide-dive segment, proposing a two-phase cooperative guidance framework for HGVs. Initially, during the glide phase, flight time and terminal error are established as optimization objectives, with an iteratively designed bank angle profile enabling simultaneous transition to the terminal dive phase for vehicles with varying initial conditions. Subsequently, during the terminal dive phase, a differential dynamic programming method incorporating step-size optimization (DDP-S) is derived to obtain baseline control inputs, and a multi-population grey wolf optimization (MP-GWO) algorithm, enhanced with an attention mechanism, is designed for cooperative planning. Finally, numerical simulations validate the reliability of the designed time-coordinated approach, as well as the performance improvements of the enhanced MP-GWO over existing bio-inspired optimization algorithms.