Space situational awareness is a constantly moving target.
Software from Sydney-based Saber Astronautics, which describes itself as a “Global space operations provider,” is rapidly spreading throughout the US military. It’s just won an extra $540,000 to meet the growing list of information the new Space Force operations command keeps discovering it needs in its ‘Space Cockpit.’
The number of users of the software in the US doubled in August with hundreds of operators in the United State Space Force using it to assist with understanding where objects like satellites are in space, and importantly where they are headed.
Sabre’s CEO, Dr Jason Held says Space Cockpit, in particular the visualizions fields:” are going a bit viral.”
Saber runs Australia’s Responsive Space Operations Centre at Lot 14 in Adelaide’s North Terrace. It’s also involved in NASA’s Moon to Mars Project and won an Australian Defence Innovation Hub contract centred on improving the nations’ space domain awareness.
Space situational awareness requires a mountain of data
The problem it solves is data.
There’s just so much of it.
And it all comes in different formats, at different times, with differing degrees of reliability.
For example, we rarely know the exact location of any given satellite.
It may get an occasional radar fix. But, unless it’s openly broadcasting its position similarly to terrestrial aircraft and shipping, its orbit is a matter of guesswork.
“That’s why when anything is predicted to travel within 1000 kilometres of another space object, one of them will have to move out of the way,” says Saber Astronautics spokeswoman Carmen Truong. “That’s a bit of a hassle as space becomes more crowded.”
“That’s why every piece of available data about that satellite has to be gathered, processed and refined. It must then be blended with other ingredients, such as local space weather conditions, before it can be baked into something useful.
“You have data from defence. You have data from private networks. You have data from government agencies. And they’re not being collated to the extent we’d prefer,” Truong says.
“We need to be able to put it all together so that someone can get a really nice, top-level view without having to take a deep dive into the code and algorithms behind it all”.
Machine learning is constantly observing what happens and comparing it to what was predicted. It’s also being used to translate raw data from a multitude of different formats and sources into a single, information-rich stream.
But that, Truong says, presents its own problems.
The reliability of each fragment of data must be assessed. And the impact of each and every margin of error must be tracked as it influences the information-sorting processes.
“Sometimes you get data that’s off the charts, and you’re like, ‘Oh, well, that might be a mistake’,” she says. “But it’s usually not that obvious.”
It’s a problem Saber is focussing on.
“We are not sure about how the final solution will present itself yet,” Truong says. “But we think verification is an untapped resource”.
One practical aspect may include creating a formalised network of on-call astronomers and tracking providers.
It’s why they’ve made their ‘pet project’ – the Terrestrial and Astronomical Rapid Observation Toolkit (TAROT) – freely available to the public.
If a satellite suddenly goes dark, the public can point their radars, telescopes and cameras at its probability bubble to see precisely where it is. This can allow a more detailed examination to determine what went wrong.
“We’d like a really nice collaborative thing where we’re working with a diverse group of people to give us a better view of the space we’re working in,” she says.