A rapid hybrid method for powered reentry trajectory planning with uncertain no-fly zone constraints

The reentry trajectory planning or optimization of a high lift-to-drag hypersonic gliding vehicle is a widely studied field. Current trajectory planning methods focus on very well-known tasks and in very well-known conditions. However, limited by maximal detection range of sensors or outdated intelligence, a key challenge is developing a fast real-time method that generating solutions for tasks in uncertain environments where traditional methods may not be available. This article seeks to combine the advantages of popular convex optimization and proposes trajectory stitching technique, to create a new approach that combines computational efficiency and optimal performance with uncertain no-fly zone constraints. Our approach first plans a baseline trajectory based on the initial guess by convex optimization. The optimized trajectory is then updated partially by an approximate algorithm once the change in the no-fly zone is detected. Furthermore, intermittent thrust is introduced to improve the maneuverability. Simulation result and the associated analysis demonstrate the potential benefit of this planning framework in reentry mission.