How to spot your satellite: a demonstration.

After much expectation, the first launch of Ariane 6 took place on 9 July 2024. The mission was designed as a rideshare, carrying multiple payloads into space. Rideshare missions have been gaining popularity because they allow the launch of small payloads at a reduced cost. They have influenced the trend of deploying large numbers of small satellites instead of large, expensive satellites in small numbers.

On the flip side, this approach has also created some challenges. When multiple objects are inserted into very similar orbits simultaneously, Space Surveillance and Tracking systems face difficulties in correlating observations and cataloging these objects accurately. Publicly available space object catalogs, such as Space-Track, depend on the collaboration of operators to update their databases, which in turn challenges satellite operators to identify and contact their own satellites.

What is the need and how do we address it?

• High data accuracy when it comes to orbit estimates and object identification.
• Fastest possible object identification.

We identified the need to follow such events closely, using our data fusion capabilities, to provide support to our customers from the moment their assets are in orbit.

Preparation is key

Preparation started weeks in advance, with an assessment of which sensors would be needed to track the objects in the target orbit, considering the intended insertion orbit and the objects' characteristics. Our data processing pipeline was set up to process all expected data automatically, and an operational timeline was defined to ensure 24-hour analyst support.

We have liftoff

After lift-off, we confirmed our insertion orbit predictions, and the tracking strategies were distributed across the team.

12 hours post liftoff

By the next morning, just 12 hours after the launch, we had already processed our first observations. This data was used to:

• Correlate the TDMs to the pre-launch TLEs
• Estimate the accuracy of TLEs from external sources
• Refine the external TLE estimations
• Generate new tracking strategies

Continuous operations

We continued to gather data during a 7-day-long observation period, observing all objects, including the tumbling Ariane-6 upper stage and the cluster of small CubeSats that stayed close together throughout the campaign. Since the initial measurements arrived much earlier than any publicly available orbital source, a track-to-track correlation algorithm was used to achieve independent accurate orbit determinations for each of the objects.

Spot the satellite

Without accurate and satellite-specific TLE, it becomes very difficult to find the satellite and therefore establish a reliable connection with it. That was exactly the case with Rapid Cubes and TU Berlin. OOV-Cube failed the initial contact attempt and the satellite was temporarily lost. Even though public sources hadn't yet identified the object, we were able to narrow the possibilities down through high-precision early orbit estimates and object association, enabling TU Berlin to establish the connection.

Learn more about OKAPI:LEOP for Launch and Early Operations, or get in touch with our team.