Entry Trajectory Optimization With Complex No-Fly Zone Constraints Using Bilinear Interpolation and Augmented MPSP

For entry trajectory optimization problems with complex no-fly zone (NFZ) constraints, this article proposes a general NFZ avoidance method. First, digital image processing is employed to represent complex NFZs as unified bilinear interpolation functions. This function determines whether the vehicle is currently within an NFZ. Then, through state augmentation, it transforms the entry trajectory optimization problem with NFZ and other path constraints into an optimal control problem (OCP) with terminal constraints only. Next, the closed-form control update for iteratively solving the transformed OCP is derived using the augmented model predictive static programming. Extensive numerical simulations are conducted to evaluate the performance of the proposed method. The results show that it can effectively handle NFZs with nonconvex shapes, irregular geometries, and complex distributions, while achieving high computational accuracy and fast solution times without relying on any solver, demonstrating strong potential for online implementation.