This work suggests a new approach to fast identify feasible profiles to simultaneously and efficiently inject into orbit multiple space assets by means of a deployer equipped with low thrust control authority. The proposed algorithm, while finding an optimal trajectory to deploy N heterogeneous satellites correctly phased on their operational orbits, aims of being computationally light and fast. The algorithm is proposed to be as flexible as possible in terms of scenarios, being compatible with both single-launch homogeneous space assets constellation and heterogeneous multi-satellites deployment, differing in final orbit insertion and physical properties. A multi objective optimization is preferred, aiming to minimize the fuel consumption and the time to operations. The low-thrust trajectory to follow between two arbitrary orbits in space is found by exploiting a 3-dimensional shape based algorithm, based on non-linear interpolation of consecutive orbits. To perform the most demanding transfers in terms of propellant and time at reasonable costs, i.e. those entailing large plane changes (i.e. Right Ascension of the Ascending Node (RAAN) and inclination), the asymmetrical Earth gravitational field induced secular variation is exploited. The paper will discuss the sensitivity analysis with respect to the variations in the optimization search space with particular attention to the computational load. A critical comparison between the adoption of a pure heuristic optimization algorithm and its hybridisation with a branch and bound approach is also discussed in terms of computation efficiency. Finally, a realistic scenario is presented to highlight the proposed approach performances when stressed in terms of both search space and in presence of constraints. The results show how this approach is suitable to deploy several satellites directly onto their operational orbit with only one launch, even when the orbits deeply differ in their keplerian elements.
Low Thrust Multi-Injection Approach for Constellation and Multi-Mission Deployment
Prinetto, J.;Lavagna, M.
2021-01-01
Abstract
This work suggests a new approach to fast identify feasible profiles to simultaneously and efficiently inject into orbit multiple space assets by means of a deployer equipped with low thrust control authority. The proposed algorithm, while finding an optimal trajectory to deploy N heterogeneous satellites correctly phased on their operational orbits, aims of being computationally light and fast. The algorithm is proposed to be as flexible as possible in terms of scenarios, being compatible with both single-launch homogeneous space assets constellation and heterogeneous multi-satellites deployment, differing in final orbit insertion and physical properties. A multi objective optimization is preferred, aiming to minimize the fuel consumption and the time to operations. The low-thrust trajectory to follow between two arbitrary orbits in space is found by exploiting a 3-dimensional shape based algorithm, based on non-linear interpolation of consecutive orbits. To perform the most demanding transfers in terms of propellant and time at reasonable costs, i.e. those entailing large plane changes (i.e. Right Ascension of the Ascending Node (RAAN) and inclination), the asymmetrical Earth gravitational field induced secular variation is exploited. The paper will discuss the sensitivity analysis with respect to the variations in the optimization search space with particular attention to the computational load. A critical comparison between the adoption of a pure heuristic optimization algorithm and its hybridisation with a branch and bound approach is also discussed in terms of computation efficiency. Finally, a realistic scenario is presented to highlight the proposed approach performances when stressed in terms of both search space and in presence of constraints. The results show how this approach is suitable to deploy several satellites directly onto their operational orbit with only one launch, even when the orbits deeply differ in their keplerian elements.| File | Dimensione | Formato | |
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