Multi-objective path optimization of a satellite for multiple active space debris removal based on a method for the travelling serviceman problem

Abstract

Space debris removal is currently a critical issue for space development. It has been reported that five pieces of debris should be removed each year to avoid further increase in the amount of debris in orbit. One approach for the removal of multiple pieces of debris is to launch multiple satellites that can each remove one target debris from orbit. The benefit of this approach is that the target debris can be removed without orbit transition, and thus, the satellite can be developed considering simple satellite mechanics. However, to realize this concept, multiple satellites need to be launched. Another approach is to use one satellite to remove multiple pieces of space debris. This approach can reduce the launch costs and achieve efficient removal of space debris. However, the satellite must change its orbit after the removal of each debris piece, and a technique for optimizing the orbit transition is required. In this study, the latter strategy and developed a satellite trajectory optimization method for efficient space debris removal were focused on. The similarity between the problem of multiple space debris removal and the travelling serviceman problem (TSP) were considered, and the TSP solution involving an evolutionary algorithm (EA) was applied. To improve the efficiency of multiple debris removal, the total radar cross-section (RCS), which indicates the amount of space debris, and the total thrust of the satellite was minimized. The TSP solution method was extended to multiple objectives by coupling it with a satellite trajectory simulation. To evaluate the developed method, a set of 100 pieces of space debris was selected from a database. The results indicated a trade-off between the total RCS and total thrust.