Risk Index for the Optimal Ranking of Active Debris Removal Targets

Abstract

The first step of any active debris removal (ADR) mission is the selection of the target. The optimal choice is to find the most dangerous debris that can be removed considering the chaser spacecraft requirements and mission constraints. After creating a catalog of the current space population in low Earth orbit (LEO), the MIT Monte Carlo Orbital Capacity Assessment Tool (MOCAT-MC) is used to simulate and predict the future space environment and the interaction among the space population. A novel performance index to quantify the criticality of each debris and the risk that it presents to the space environment is proposed. The new risk index considers the proximity of the debris to highly populated regions, its persistence in orbit, its likelihood to collide, and the estimated number and mass of debris that it can generate. The risk index is then optimized to work either with the full space population or a subset of it, where the ranking of risk among debris is highlighted. Multiple risk analyses are proposed in the test cases, where the ranked list of optimal targets is provided.