Reentry predicted guidance algorithm for reusable launch vehicles based on density estimation

Follow the characteristics of multi-constraints reentry guidance for reusable launch vehicles (RLV), a new method of reentry guidance algorithm is put forward based on estimation of the density. With the technique of parameter-discriminated, the algorithm would find out the current condition of aerosphere. Further more, the algorithm could generate reasonable bank angle profiles with the consideration of path constraints such as heat rate flow, normal load and dynamic pressure. The predicted terminal location is then compared to normal condition, and the mismatch would be used to generate the magnitude of bank angle. Combining with lateral bank reversals, the on-line design of reentry guidance is completed finally. Simulation results demonstrate the effectiveness of the algorithm on achieving desired final conditions for different reentry initial conditions and atmospheric uncertainty.