Descrizione del progetto
Uno strumento intelligente per i satelliti
Una nuova generazione di satelliti completamente flessibili sta conquistando il mercato del segmento spaziale. Per controllare i carichi utili flessibili dei satelliti e le loro controparti configurabili tradizionali, il progetto ATRIA, finanziato dall’UE, costruirà uno strumento generico intelligente chiamato AI-PCS. Le tecniche di IA doteranno lo strumento dell’intelligenza necessaria a decidere in modo autonomo la configurazione ottimale delle risorse satellitari disponibili per le richieste di servizi on-demand. Un dispositivo noto come processore digitale trasparente costituirà il fulcro di questi carichi utili digitali, fornendo loro nuove capacità nell’ambito degli ultimi paradigmi rivoluzionari di rete 5G che non sarebbe stato possibile ottenere con i carichi utili analogici tradizionali, come la larghezza di banda adattativa e l’allocazione della potenza, nonché la flessibilità della connettività e della copertura.
Obiettivo
A new generation of completely flexible satellites in terms of mission definition is currently appearing in the space segment as a response to the 5G revolution, resulting in an unprecedented integration of the satellite services with the terrestrial deployments. In this context, the Digital Transparent Processor (DTP) is aimed to constitute the core of these digital payload, providing them with new capabilities unthinkable to achieve with the traditional analogue ones, such as adaptive bandwidth (BW) and power allocation, or flexibility in the connectivity and coverage.
As a consequence, the flexibility offered by these kind of satellites leads to the increased complexity in their management. Then, the optimum reconfiguration of these complex payloads to fulfil the users requirements is no longer an achievable task for a payload engineer due to the real-time constraints and the number of possibilities. To solve this, these satellites require new and intelligent tools capable of optimally allocating the satellite resources, while monitoring the interferences in such a dynamic scenario.
In this point, Artificial Intelligence/Machine Learning (AI/ML) algorithms appear to substitute the operator decisions and manual operations while configuring the payloads. In atria project, these algorithms will compose an AI/ML module in a Payload optimization Control System (AI-PCS). The algorithms are to be trained with both real data sets of former manual operations and synthetic data. Also, the algorithms will receive information from external services to provide them with inputs regarding meteorology, traffic, availability, etc. in order to achieve the optimum decisions.
AI-PCS is to be validated using both a flexible payload emulator and real satellite environments. AI-PCS is aimed to be a generic tool, transparent to the payload, providing the satcom operators with added value and turning it into a cost-effective solution for the future of the ground segment.
Campo scientifico
- natural sciencesearth and related environmental sciencesatmospheric sciencesmeteorology
- engineering and technologyelectrical engineering, electronic engineering, information engineeringinformation engineeringtelecommunicationstelecommunications networksmobile network5G
- engineering and technologyelectrical engineering, electronic engineering, information engineeringelectronic engineeringcontrol systems
- engineering and technologymechanical engineeringvehicle engineeringaerospace engineeringsatellite technology
- natural sciencescomputer and information sciencesartificial intelligencemachine learning
Parole chiave
Programma(i)
Meccanismo di finanziamento
RIA - Research and Innovation actionCoordinatore
28760 Tres Cantos
Spagna