Decentralized Operational Framework for Autonomous Space Traffic Management in High-Drag VLEO Environments

The rapid expansion of Very Low Earth Orbit (VLEO) constellations introduces significant complexities in orbital maintenance due to non-conservative forces, primarily stochastic atmospheric drag. Traditional centralized Space Traffic Management (STM) architectures, which rely on batch-processed updates and human-in-the-loop decision making, are increasingly incapable of managing the high-frequency station-keeping maneuvers required in these altitudes. This paper investigates the adaptation of the Low Altitude Traffic Management System (LATMUS) framework for the space domain to provide a decentralized, asynchronous solution for VLEO safety.

The proposed architecture leverages a distributed Machine-to-Machine (M2M) protocol where satellite operators interact through specialized Service Suppliers. This study evaluates the integration of Supplemental Data Suppliers (SDS) that provide real-time thermospheric density forecasts. By incorporating these high-fidelity models, the system can predict drag-induced orbital decay variations during solar flux events (F10.7 index spikes) and automatically propagate these uncertainties into conjunction assessment algorithms. This allows for automated deconfliction without the latency inherent in centralized ground control systems.

By utilizing the LATMUS-derived intent-sharing protocol, operators can perform collision avoidance while maintaining state-vector privacy and minimizing data leakage. Numerical simulations involving a dense 3U CubeSat constellation demonstrate that this decentralized approach reduces the computational overhead of conjunction screenings by 70 percent compared to legacy systems. The findings suggest that adopting a distributed traffic management paradigm is a prerequisite for the operational scalability of VLEO missions, ensuring both safety and strategic autonomy for next-generation orbital infrastructure.