Neuraspace introduces “Machine Learning Prediction Plots” for earlier collision avoidance planning

Neuraspace, a European-born global leader in space traffic management (STM), has introduced “Machine Learning Prediction Plots”, giving satellite and satellite constellation operators a tool for earlier collision avoidance planning.

As a first in the space industry, the latest addition to Neuraspace’s STM software, using artificial intelligence (AI), enables operators to decide several days earlier whether to proceed with the available data or wait for additional data before making preparations for a collision avoidance manoeuvre. It gives them the means to decide if the data is good enough to make a decision.

As a result, operators, in particular those operating constellations with dozens or hundreds of satellites, have more decision time and can extend their satellites lifespan by saving valuable fuel and avoiding unnecessary manoeuvres.

Chiara Manfletti, director and chief operating officer of Neuraspace, said: “Neuraspace is the first STM company introducing “Machine Learning Prediction Plots”. Until now, no space traffic management tool was capable of making such an important forecast.

“Satellite operators already receive a deluge of alerts, most of them false, and therefore perform many unnecessary but costly manoeuvres. A 300-satellite constellation may receive about 580 alerts, requiring human intervention and satellite manoeuvres, per year. With an emergency manoeuvre in LEO costing about €25,000, this adds up to a staggering cost of €14 million per year. Saving some of these immense costs will make a huge impact.”

Neuraspace’s “Machine Learning Prediction Plots” calculate the path and forecast possible positions of the objects involved in a conjunction at the time of closest approach (TCA). Customers of the Portuguese company can access this information either through Neuraspace’s API or its website application.

Only made available last year, Neuraspace’s advanced space debris monitoring and satellite collision avoidance system is already being tested by some of the biggest satellite operators in the world.

“With the existing huge amount of space debris and the expected growth of space traffic in LEO, the future evolution of the space industry will become uncertain, inefficient, and costly if not addressed,” Manfletti said.

ENDS

Note to editors
Attached image: Chiara Manfletti, director and chief operating officer of Neuraspace

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About Neuraspace
Neuraspace is developing an advanced system for monitoring and preventing collisions in space. Neuraspace has raised 2.5 million euro from Armilar Venture Partners and a further 25 million euro for sensor infrastructure and its growth strategy with the support of the Recovery and Resilience Plan and NextGeneration EU Funds. The Neuraspace platform solves the issue of space traffic at large through an end-to-end automated solution built on three key pillars: data fusion, artificial intelligence and machine learning,