Daniel Jang, Massachusetts Institute of Technology; Peng Mun Siew, Massachusetts Institute of Technology; Pablo Machuca, Massachusetts Institute of Technology; Richard Linares, Massachusetts Institute of Technology
Keywords: Lethal Non-trackable Objects, Monte Carlo methods, on-orbit collisions, Break-up events orbital capacity, low-earth orbit environment
Abstract:
Methods for accurate estimation of the future LEO population due to launches, collisions, and orbital perturbations can be largely be divided into two methods – Source Sink Evolutionary models (SSEM) and Monte Carlo (MC) methods. SSEM categorizes all modeled resident space object (RSO) into a few categories and represents the evolution of the population with coupled ODEs per altitude shell deterministically. MC method is a sampling-based method that propagates all objects orbital states at some discrete time steps and determines collisions resulting in some collision dynamics. Many scenarios are propagated this way with some random sampling of parameters at initialization and
during run-time, such as the physical properties and orbital states of the objects and allocation of debris and traffic patterns.
MIT Orbital Capacity Tool (MOCAT) has been developed with both methods to leverage the SSEM methods simplicity and computational efficiency and also the MC methods comprehensiveness. The MC model is called MOCAT-MC, which has been developed to analyze the future LEO population in a modular and computationally efficient manner
and to understand the future orbital environment and to validate other types of evolutionary models. While computationally expensive, satellite users and SSA organizations currently use MC-like methods to predict conjunctions and plan conjunction avoidance maneuvers due to its fidelity and flexibility. The main reason behind the development
of the MOCAT-MC is to provide in the end an open-source software, which can be accessed and employed by the scientific community. Particular regard is given to the computational speed of all the blocks of the MOCAT-MC.
One of the drawbacks of MC methods is the high computational time required to run the simulations, which prevents these software to be tested against many different scenarios in terms of initial population, launch rate, collision and explosion events occurrences, etc. Modeling the future population and traffic of LEO is important in understanding the requirements put on the SSA community. Mature development of a validated model such as MOCAT-MC will allow for understanding of the changes to the requirements on the SSA community for a safe operation in space. In this paper, the capabilities of the sub-modules of MOCAT-MC is described and analyzed for their fidelity and computational efficiency. The MC scenario results are tested against different future launches scenarios to assess the evolution of the LEO population. Several variations for the sub-modules and assumptions are considered, such as various atmospheric model, propagator fidelity, active satellite station-keeping policies, new launches, reentry, post-mission disposal, explosions and collisions. Fragmentation effects are modeled as a modified version of the NASA standard break-up model. The proposed MOCAT-MC is tested with different launch rate scenarios, including the “no future launches” scenario. Performance and accuracy are analyzed and discussed in this paper, including the sampling-based and deterministic collision statistics, comparison to historic data on collisions, overall all-vs-all LEO population performance, and the effect of propagator fidelity with varying orbital perturbations. Variation to the time-step and collision cube size and shape are analyzed. The assumed future launch profile and the parameters of payloads are varied. Policies at the national and international level are examined to understand the effect, such as the recent 5-year deorbit rule and its effect on the orbital rain experienced by the VLEO operators. Lastly, the effect of an increased LEO population near the orbital capacity is analyzed for increased computational load placed on the SSA operators in terms of conjunction assessment, association and correlation issues, uncorrelated target processing and data processing computation requirements. Many of the existing research-level MC models are created by national space organizations and corporations and are close-sourced. MOCAT is an open-source tool such that researchers can use a common model that is validated, robust, and efficient, allowing for collaboration amongst the community who are interested in using and developing this tool for a safer space operation.
Date of Conference: September 19-22, 2023
Track: Space Debris