Neuraspace Enhances Space Traffic Management Through EISCAT Partnership

Neuraspace Enhances Space Traffic Management Through EISCAT Partnership
by Hugo Ritmico
Madrid, Spain (SPX) Aug 16, 2024
Neuraspace has expanded its network of partners by joining the EISCAT Scientific Association as an affiliate institution. EISCAT Scientific Association, known for providing high-latitude incoherent radar scattering facilities for scientific research since the 1980s, will now collaborate with Neuraspace, a leading European company in space traffic management (STM).

This collaboration grants Neuraspace access to EISCAT's radar observation capabilities, which are crucial for monitoring space objects. Additionally, Neuraspace will gain valuable ionospheric and atmospheric data, aiding in the preparation for the future use of EISCAT_3D, the next-generation incoherent scatter radar system.

By integrating EISCAT's radar data with its own optical data, Neuraspace aims to offer a more complete understanding of the space environment. This will enhance the company's ability to automate operations, suggest maneuvers, and improve decision-making processes for its customers.

"Access to EISCAT data is a game-changer for Neuraspace," said Chiara Manfletti, CEO of Neuraspace. "We can develop more robust methodologies and algorithms to correlate information from various sources. This ultimately leads to actionable intelligence for automated operations incorporating space traffic management. EISCAT's expertise and commitment to scientific progress aligns perfectly with our mission. Their future endeavours, such as EISCAT 3D, further solidify this partnership's potential."

The partnership with EISCAT also opens the door for Neuraspace to collaborate with a broader community of experts, promoting innovation in STEM research and development.

Dr. Thomas Ulich, head of science at the EISCAT Scientific Association, commented, "Maintaining accessible orbits is critical to societal functions. Our data will empower Neuraspace to refine object tracking and optimise space operations."

EISCAT's historical data on catalogued space objects will be particularly useful for Neuraspace as it develops new machine-learning algorithms. These algorithms will help improve the taxonomy of space objects, predict their behavior more accurately, and identify patterns.

The insights gathered from EISCAT's data will be integrated into Neuraspace's STM solution, providing customers with better-informed decision-making tools. Neuraspace already offers predictions on the evolution of object uncertainty up to five days ahead of a close approach.

The EISCAT Scientific Association is nearing the completion of its EISCAT 3D system, an advanced radar facility in the Arctic. The first test measurements with EISCAT 3D are expected to begin next year.