Projektbeschreibung
Ein intelligentes Instrument für Satelliten
Eine neue Generation von uneingeschränkt flexiblen Satelliten ist dabei, das Weltraumsegment zu erobern. Um flexible Satellitennutzlasten und ihre konfigurierbaren traditionellen Pendants zu kontrollieren, wird das EU-finanzierte Projekt ATRIA ein generisches, intelligentes Instrument namens AI-PCS entwickeln. Mithilfe von Techniken der künstlichen Intelligenz soll AI-PCS in der Lage sein, selbstständig über die optimale Konfiguration der verfügbaren Satellitenquellen für angeforderte Dienstanfragen zu entscheiden. Der digitale transparente Prozessor wird das Kernstück für diese digitalen Nutzlasten bilden. Damit werden neue Fähigkeiten innerhalb der revolutionären jüngsten 5G-Netzwerkparadigmen möglich, die mit traditionellen analogen Nutzlasten nicht denkbar gewesen wären, wie etwa eine adaptive Bandbreitenzuordnung und Leistungszuteilung sowie Flexibilität bei der Konnektivität und Abdeckung.
Ziel
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.
Wissenschaftliches Gebiet
- 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
Schlüsselbegriffe
Programm/Programme
Aufforderung zur Vorschlagseinreichung
Andere Projekte für diesen Aufruf anzeigenUnterauftrag
H2020-SPACE-2020
Finanzierungsplan
RIA - Research and Innovation actionKoordinator
28760 Tres Cantos
Spanien