Dr Marco Rocchetto, CEO of Spaceflux, explains how space situational awareness (SSA) underpins the growing efforts to remove debris from orbit.
Once seen as science fiction, cleaning up space has become one of the most pressing engineering and policy challenges of the space age. With thousands of satellites launching each year, orbital congestion is rising. The European Space Agency estimates over 40,000 trackable objects larger than 10 cm, plus millions of smaller fragments, travel at speeds up to 28,000 km/h. Even tiny paint flecks can damage spacecraft at such velocities.
From Awareness to Action
Before any debris can be captured, nudged, or deorbited, operators must first detect, track, and understand it. SSA provides this foundational knowledge by revealing the location, movement, and changes in orbiting objects.
Historically, space safety focused on collision avoidance, guiding satellites to manoeuvre away from hazards. Today, attention has shifted toward active debris removal (ADR), which involves capturing defunct satellites and removing them from orbit. Initiatives like ClearSpace-1, Astroscale’s ELSA-M, and OrbitGuardians’ ADRAS-J are already testing these technologies.
Even with advanced robotics, every ADR mission begins with SSA. Operators must know a target’s position, rotation, and stability before approaching safely.
Seeing Before Cleaning
High-quality SSA data answers three key questions:
- Location: Where is the debris, and how is its orbit changing?
- Behaviour: Is it tumbling, drifting, or stable?
- Environment: Are other objects nearby that could interfere with removal?
Optical telescope networks, like Spaceflux’s global array, track objects across low Earth orbit (LEO), geostationary orbit (GEO), and cislunar space. These systems capture brightness, motion, and orientation, producing detailed signatures of size, shape, rotation, and stability.
This information allows removal teams to plan safe trajectories and anticipate debris response. Without SSA, even sophisticated ADR vehicles would be operating blindly.
Precision Matters
In orbital cleanup, accuracy is critical. Small errors can turn missions into costly failures. SSA, enhanced by AI analytics, tracks objects with sub-arcsecond precision, far beyond traditional two-line element (TLE) data. AI models:
- Forecast motion influenced by drag or radiation pressure
- Detect fragmentation events affecting rotation or mass
- Recommend optimal approach windows for safe capture
These predictive capabilities turn debris removal from an experimental idea into a practical operation.
Building a Collaborative Ecosystem
No single entity can tackle orbital debris alone. A functional ecosystem requires collaboration among SSA providers, ADR operators, regulators, and insurers.
- SSA data underpins mission planning
- ADR operators design safe capture trajectories
- Regulators and insurers use SSA to verify risk reduction
Standardized data sharing and secure interfaces enable a unified view, balancing competition with collective responsibility.
Technology in Action
Removal methods vary by debris type:
- Robotic arms or magnetic plates for intact satellites
- Nets or harpoons for irregular fragments
- Laser nudging or ion-beam shepherding for contactless movement
- Drag sails and tethers to accelerate re-entry
All methods rely on accurate SSA data for precise execution.
Data as Accountability and Currency
SSA also supports policy, insurance, and commercial models. Verified debris removal can enable pay-per-kilogram frameworks, turning data into a measure of accountability and value.
The Path Forward
Future missions will integrate real-time SSA networks with autonomous cleanup systems. Trusted, interoperable data standards will ensure satellites, sensors, and ADR providers operate seamlessly.
Ultimately, SSA is not just a support tool—it is the foundation of orbital cleanup. Precision data enables informed decisions, turning tracking into actionable removal, and securing space for generations to come.
