Dr. Marco Rocchetto, CEO of Spaceflux, discusses the role of space situational awareness in advancing the removal of debris from space.
The idea of cleaning up the universe was once considered the stuff of science fiction. Today, it is one of the most urgent engineering and policy challenges of the space age.
Thousands of new satellites are launched every year, making orbits even more crowded. The European Space Agency estimates that there are currently more than 40,000 trackable objects larger than 10 centimeters, and millions of smaller pieces moving at speeds of 28,000 km/h. At that speed, even paint chips could affect the spacecraft.
Removing debris from orbit is essential to preserving space as a shared, sustainable environment. But before we can capture, poke, or deorbit debris, we must first find it, track it, and understand it. Information about where objects are, what they are doing, and how they are changing comes from spatial situational awareness (SSA) data.
At the heart of any cleanup mission is data tracking and analysis. And the better the data, the safer and more successful orbit repair will be.
From awareness to action
For decades, space safety has focused on avoidance, monitoring for potential collisions and moving active satellites away from danger.
Attention is now turning to active debris removal (ADR). This involves physically capturing and removing defunct hardware from orbit. Projects such as ClearSpace-1, Astroscale’s ELSA-M, and OrbitGuardians’ ADRAS-J demonstrate technology that can grab, tow, and deorbit dead satellites.
But no matter how advanced robotics and propulsion systems become, every removal mission begins with an SSA. Operators need to know where the target is, how it will move, and its condition before approaching safely. In this sense, SSA is more than just a support function; it is the basis for cleanup.
View before cleaning
High-quality SSA data answers three important questions:
Location: Where exactly is the target and how is its trajectory evolving? Behavior: Is it rolling, floating, or stable? Environment: Are there other objects nearby that could impede removal attempts?
Optical networks, such as Spaceflux’s global telescope array, provide continuous, high-precision tracking throughout low Earth orbit (LEO), geostationary orbit (GEO), and even lunar and stellar space.
Each telescope measures an object’s brightness, movement, and orientation over time, producing detailed signatures that reveal its size, shape, rotation, and stability.
This data allows removal teams to determine the safest entry trajectory and predict how the object will react to capture. Without this foundation, even the most sophisticated debris removal spacecraft cannot operate in the dark.
The need for precision
Precision is everything in orbital cleanup. A difference of just a few meters in prediction can make the difference between a successful capture and a costly failure. Optical SSA data, refined through AI-based analysis, can track objects with sub-arcsecond accuracy, far exceeding the positional accuracy of traditional two-line element (TLE) data.
The AI model processes the raw sensor data, removes atmospheric noise, and continuously updates the trajectory solution. They can:
Predict the movement of debris affected by atmospheric resistance and radiation pressure. Detect fragmentation events that change an object’s spin or mass distribution. Recommend optimal approach windows for safe rendezvous and capture.
These predictive capabilities transform debris removal from an experimental concept to an operational reality.
Building a collaborative ecosystem
No single organization can tackle the debris problem alone. The emerging orbital sustainability ecosystem relies on partnerships between data providers, removal operators, regulators, and insurance companies.
SSA providers such as Spaceflux provide continuous data streams and predictive models to support mission planning. ADR operators use these insights to design capture trajectories and ensure mission safety. Agents and insurance companies use SSA data to confirm that items have been removed and quantify risk mitigation.
This collaboration allows all actors to work from a common interface by standardizing data formats and sharing access through secure interfaces. It is a model of open coordination that balances commercial competition and collective responsibility.
Leveraging technology
Removal technology has advanced rapidly in recent years. Different concepts are suitable for different types of debris.
A robotic arm or magnetic docking plate for large intact satellites. Nets and harpoons for irregular and rotating debris. Push objects without physical contact by laser nudging or ion beam shepherding. Once the capture is complete, drag the sail and tether to accelerate reentry.
Each of these options is dependent on accurate SSA data. For example, a laser nudge platform must know the exact rotational speed and surface reflectance of the target in order to deliver the appropriate impact. Robotic capture vehicles require accurate models of angular momentum to avoid instability during docking.
In all cases, SSA provides parameters that make the mission safe. It is a silent but essential partner in any ADR mission.
Responsibility and cleaning economy
SSA data also plays an important role in policy, insurance, and economics. As orbital sustainability regulations evolve, operators will increasingly need to verify compliance and demonstrate that debris was safely deorbited and that mission activities reduced the risk of collision.
ADR also opens the door to a new commercial model in which governments and consortiums pay a fee for each kilogram of debris removed, with verification from third-party SSA observations. In such a framework, data becomes more than just an enabler, it becomes a currency of accountability.
The way forward: unified stewardship
Looking to the future, the line between monitoring and action will become increasingly blurred. The next-generation cleanup mission will operate in parallel with the real-time SSA network and utilize continuous data feeds to autonomously adjust its trajectory.
As these systems mature, the focus will shift from individual missions to a persistent, integrated approach: a living data infrastructure that monitors, predicts, and supports large-scale orbital remediation.
To enable this, the space community requires reliable, transparent, and interoperable data standards that allow all satellite operators, sensor networks, and ADR providers to speak the same technical language.
Only then can orbital cleanup be moved from demonstration to everyday practice.
Conclusion: Data as the foundation for cleanup
Cleaning up your space isn’t just an engineering challenge. It’s an information challenge. The real difficulty lies not in the mechanism of capture, but in the knowledge that precedes capture: knowing exactly where the debris is, how it is behaving, and how it is changing.
As the space economy expands, SSA will continue to be the foundation for all remediation efforts. From initial optical detection to final validation of reentry, data ensures that orbital cleanup is based on informed decisions rather than uncertainty.
The universe is vast, but precision is what keeps it safe. Through intelligent use of data and collaboration across the industry, we can move from simply tracking debris to truly cleaning the orbital environment and preserving it for future generations.
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