Project Description

The AI FIGHTS SPACE DEBRIS project aims to contribute to the Neuraspace Space Traffic Management Platform, the first spaceops platform addressing Collision Avoidance. Space as a market, especially new space, will present new challenges, and new needs that will require new tools. Within the PRR project it is planned to develop all the necessary tools that a satellite operator needs to perform space operations and maintain the space access safety and sustainability. These tools will be made available through Neuraspace’s platform as a stand-alone product or in an integrated suite that provides a higher added value.

Neuraspace has a new and unique product based on AI and Data Fusion, to ensure a better solution for Space Traffic Management (STM) and to ensure Sustainable Space. The Neuraspace platform is designed to reduce false alerts, therefore reducing unnecessary manoeuvres, which will save up to 25 k€ per manoeuvre. AI-powered manoeuvres improve the customer’s asset investment by lowering risk, saving fuel/extending satellite lifespan, and constraint/priority based manoeuvres; the platform will also include AI tools to reduce staff time on these operations (business focus).

The target customers are satellite operators facing the space operations challenges, and other stakeholders in need of these services, e.g insurance providers for satellite operators, software providers and regulators.

Project Structure

Project Structure

The products that will be developed over the course of the PRR project are focused on a unique AI/ML solution that tracks satellites, detects potential collisions and fights space debris. The project is divided in five Product, Process and Services (PPS); the work performed from PSS#1 to PSS#4 pertains to the Neuraspace platform, whilst PSS#5 is complementary to the platform and encompasses the entire body of knowledge related to Space Traffic Management generated over the course of this PRR project.

• PPS1: Neuraspace Sensor and Events Catalogue

What: Tracks space objects and keeps track of the possible near encounter by creating Collision Data Message

Why: Increases planning margin as alerts come earlier. Generates savings, as better predictions reduce the need of staff allocated to the tasks (false alerts reduction). Having an end-to-end service that tracks objects with radars and verifies their safety regarding close encounters is essential to obtain a competitive advantage in this market.

• PPS2: Neuraspace AI Risk Predictor:

What: Receives Collision Data Messages of a client’s asset(s) and provides a complete analysis and visualisation of the encounter.

Why: More informed decisions reduce risk and allows savings by avoiding unnecessary manoeuvres (one emergency manoeuvre for a single satellite in LEO can cost around 25 k€).

• PPS3: Neuraspace AI Risk Mitigator:

What: Suggests the best possible manoeuvres according to technical and business criteria.

Why: Less staff/less time involved in the decisions (operation cost savings) and AI supporting the team to take better decisions.

• PPS4: Resident Space Objects Visualisation Tool

What: User-friendly interface that allows to easily visualise the positioning of the space objects as well as close encounter predictions.

Why: Complex decision making requires easily accessible information with the help of better tools for asset visualisation, allowing quicker and more informed decisions at all levels of the organisation.

• PPS5: Space Traffic Management Body of Knowledge

What: State of the art knowledge in Space Traffic Management (STM) through the specialized courses, research papers, master thesis, executive training, and support to start-ups.

Why: Transversal PSS producing knowledge for the others PSS and the STM value chain.

These products will be developed over 36 months by the consortium composed of Neuraspace as leader, IST, UNL-FCT, UC, IPN and GMV, all with expertise in key areas for the successful execution of the project.

The project follows the work breakdown structure presented in Figure 1, where it is possible to see the division of works by the consortium, contemplating all the products (PSS) previously presented.