Missions for Removal of Orbital Debris

During the last 40 years, the number of artificial objects in orbit increased quite steadily, leading to a big problem to be dealt at present and in near future. Most of these objects correspond to space debris in LEO which represent a latent threat to all the missions performed in such a region. Current studies suggest that to mitigate this problem as effective as possible, active debris removal (ADR) must be carried out in the following years. In this line, this strategy of debris removal needs to be done in the most efficient way, needing deep analysis of each mission. This thesis analyses the validity and versatility of an algorithm capable of finding optimal solutions for the manoeuvres involved in the active debris removal missions. Due to the great number of possibilities that the mission could have, the algorithm has been developed as a genetic algorithm. The work analyses how an ADR mission could remove target debris which correspond to some stages of the Russian rockets from the family Cosmos. With this approach, the algorithm was able to demonstrate its ability to find different possible sequences of debris to be deleted, not being far away from the best solution reached. The best solutions where the vehicle that must remove several objects from orbit can be considered in terms of fuel consumption, in terms of mission time or taking these two parameters into consideration. In addition, it also probed its good behaviour when changing the number of space debris to be deleted, together with variations in the problem parameters. In fact, the algorithm versatility enables this tool to be used with other target debris, and hence, to be implemented in different active removal debris missions.