Performance of Space Debris Removal Satellite Considering Total Thrust by Evolutionary Algorithm

Abstract

Space debris mitigation is a key technology for space development. Further increase in the amount of debris can be avoided if five pieces of debris is removed every year. One concept to remove multiple pieces of debris is to use a satellite. This approach can reduce the launch cost and remove space debris efficiently compared to using multiple satellite that removes one piece of debris. To realize this concept, an optimization technique for orbit transition is required. This study develops a satellite trajectory optimization using evolutionary algorithms (EAs). The travelling serviceman problem's (TSP) solution of EA is applied considering the similarity between the two. The TSP solution method is extended by coupling it with a satellite trajectory simulation. To improve the efficiency for multiple debris removal, the maximization of the total radar cross-section (RCS) is considered that indicates the amount of space debris as an objective function. The total fuel consumption of the satellite is calculated by considering the total velocity increment as a constraint. To evaluate the developed method, a set of 2000 pieces of space debris were selected from a database, and five cases were solved by changing the total velocity increment by 20 m/s, 40 m/s, 60 m/s, and infinity. As a result, RCS was reduced as the total velocity increments were reduced. Trends of solutions obtained through the EA process were visualized using scatter plot matrix.