Development and Validation of an Enhanced Risk-Driven Index for Active Debris Removal Prioritization

The growing number of space debris in low Earth orbit (LEO) jeopardizes long-term orbital sustainability, requiring efficient risk assessment for active debris removal (ADR) missions. This study presents the development and validation of Filtered Modified MITRI (FMM), an enhanced risk index that ranks debris, incorporating a proactive fictitious collision model and a dynamic background density within a concurrent analysis framework. Using the MIT Monte Carlo Orbital Capacity Assessment Tool (MOCAT-MC) simulation framework, we performed a comprehensive performance evaluation and sensitivity analysis to probe the robustness of the FMM formulation. The results show that, while FMM provides superior identification of high-risk targets, with a near-perfect identification rate for objects with a high statistical probability of collision, there is a critical performance tradeoff: the event-based MITRI index, despite the lower predictive accuracy, consistently proved more effective in reducing the long-term debris population. This finding reveals a divergence between accurately predicting individual collisions and effectively mitigating long-term environmental instability. The analysis also reveals that physically grounded mass terms are necessary for a feasible risk assessment. By leveraging the open-source MOCAT-MC framework and offering a validated methodology that provides critical insights into risk dynamics, this research enhances our ability to select optimal ADR targets and ensure the long-term viability of LEO operations.