Trajectory Optimization Approach for Adaptive Multiple-Pass Aeroassisted Orbital Maneuver
Aeroassisted orbital maneuver changes the energy and orbit of a vehicle by traversing the planetary atmosphere. It is an essential method for achieving low-energy orbit transfer, and multipass aeroassisted orbital maneuver has been the most common type of practical application due to lower vehicle protection needs and safer atmospheric flight. The deorbit continuous thrust maneuver, multipass atmospheric flight, and insertion thrust maneuver are all simultaneously taken into account by the segmented hierarchical trajectory optimization method presented in this study. A unified optimization model for the deorbit and insertion maneuver optimization problems is constructed, and sequential convex optimization is used to solve them. In order to implement the autonomous design of the multipass atmospheric flight trajectory, the number of atmospheric flight passes and the path constraint boundaries are created into a nonlinear mapping relationship. To enable consistent modeling and effective optimization of the multipass aeroassisted orbital maneuver trajectories, a 2-level segmented step-by-step optimization framework is established. Additionally, the algorithm ensures the generality of any number of passes and constraint settings, which provides the algorithm’s robustness and migrability. As a result, it can be applied as a decision-making open loop of multipass aeroassisted orbital maneuver guidance.
Authors
- Baojun Pang (ORCID: https://orcid.org/0009-0003-6990-8682)
- Ji‐Lin Chen (ORCID: https://orcid.org/0000-0003-3223-4613)
- Hongwei Han (ORCID: https://orcid.org/0000-0003-2233-5883)
- Rui Teng
Institutions
- Beijing Institute of Technology (CN)
- Universitat Politècnica de Catalunya (ES)
Publication Details
- Journal
- Space Science & Technology
- Published
- 2025-01-01
- DOI
- https://doi.org/10.34133/space.0240
- Citations
- 1
- Primary Topic
- Aerospace Engineering and Control Systems
- Type
- article
- Field-Weighted Citation Impact
- 4.99