Space Traffic Management (STM)

Author: Tianjiang Talk
Site: https://cislunarspace.cn

Definition

Space Traffic Management (STM) is a comprehensive management and technical system covering space object awareness, orbit prediction, collision risk assessment, avoidance decision-making, and coordinated execution. It aims to ensure the safety and sustainability of space activities in an increasingly congested orbital environment.

The STM concept draws an analogy to Air Traffic Management (ATM), but due to the highly nonlinear nature of orbital dynamics, the diversity of perturbation sources (atmospheric drag, solar radiation pressure, third-body gravity, etc.), and the lack of a globally covered sensing system comparable to ground-based radar networks in space, its technical complexity far exceeds that of air traffic management.

Key Components

Space Situational Awareness (SSA)

SSA serves as the perception layer of STM, responsible for detecting, tracking, and cataloging space objects in orbit (including spacecraft, rocket bodies, and debris). Main technical approaches include:

Ground-based radar: Provides routine tracking of low-Earth-orbit targets, with good coverage and accuracy for orbits below 1,000 km.
Space-based optical sensors: Deployed in medium-high Earth orbit or geostationary orbit for optical detection and orbit determination of deep-space debris and GEO objects, compensating for ground-based radar coverage blind spots.
Inter-satellite collaborative observation: Uses multi-satellite space-based observation networks to achieve multi-angle simultaneous precision tracking.

Currently, the US Space Surveillance Network (SSN) has cataloged more than 30,000 objects in orbit (larger than 10 cm), while the estimated number of untrackable debris larger than 1 cm exceeds one million.

High-Precision Atmospheric Density Detection and Modeling

Orbital decay of low-Earth-orbit space objects is primarily determined by atmospheric drag, and atmospheric drag calculation depends on the precise knowledge of upper atmosphere density.

Traditional atmospheric models (such as NRLMSISE-00 and JB2008) have short-term prediction errors of approximately 15%-30% for atmospheric density under moderate geomagnetic activity, with errors exceeding 100% during geomagnetic storms. New-generation multi-satellite multi-source collaborative detection schemes use in-orbit accelerometers and GNSS precision orbit determination data from numerous satellites in low-orbit constellations, combined with machine learning assimilation methods, to significantly improve short-term atmospheric density forecast accuracy, thereby enhancing the reliability of orbit prediction and collision probability calculations.

Orbit Prediction and Collision Risk Assessment

Based on precise sensing and atmospheric modeling, STM requires medium-to-short-term (1-7 days) high-precision orbit prediction for all cataloged objects, and performs Probability of Collision ( $P_c$ ) calculations when predicted conjunction events occur.

A typical collision avoidance decision process is: $P_c$ > red threshold (e.g., $10^{-4}$ ) → Generate avoidance plan → Evaluate maneuver cost (propellant consumption and mission impact) → Coordinated decision (which party executes the maneuver) → Execute avoidance maneuver → Post-event assessment.

Dynamic "Space Road" Generation

In scenarios where large constellations are densely deployed, researchers have proposed the concept of "Space Roads" or "Orbital Slots" — pre-designed dynamic, protected orbital separation corridors for batch-deployed satellite constellations, reducing frequent collision avoidance maneuvers and fuel consumption for maintaining orbital configuration. Essentially, "Space Road" generation is a large-scale constrained optimization problem requiring multi-objective trade-offs among orbital mechanics constraints, mission requirements, fuel budget, and collision safety margins.

Challenges in Complex Environments

Space Weather Events: Intense solar storms and geomagnetic storms cause severe disturbances in upper atmosphere density (sometimes increasing by tens of times within hours), leading to explosive orbital decay of low-Earth-orbit targets and significantly increasing uncertainty in collision probability calculations.
Mega-Constellation Mutual Interference: Mega-constellations comprising tens of thousands of satellites not only increase in-orbit object density but also introduce unpredictable orbital deviations due to frequent orbital maneuvers, posing a "dimensionality challenge" to conventional STM systems.
International Coordination and Norms: Effective STM implementation relies on the establishment of international rules and technical standards. Currently, unified international legal frameworks are lacking in areas such as avoidance responsibility allocation and data sharing protocols.

References

2026 Aerospace Science and Technology Problems and Challenges Released, China Space Conference (CSC2026), 2026.
Ailor W H, Patera R P. Space traffic management[C]. IAC, 2018.
Emmert J T, et al. NRLMSIS 2.0: A whole-atmosphere empirical model of temperature and neutral species densities[J]. Earth and Space Science, 2021.
Bussy-Virat C D, et al. Effects of uncertain atmospheric density on collision probability[J]. Journal of Spacecraft and Rockets, 2018.