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New-Space Services

CENSSS will use data from available satellites and from new satellites to develop new exploitation models, applications and services.

Aims and Goals

One of the main objectives for this project is to use data from available satellites and from new satellites to develop new exploitation models, applica- tions and services.

 

There are many possibilities for developing on-ground services from existing satellite data, such as from the Copernicus pro- gram. Or, to develop on-board processing capabilities to work together with the new sensor and satellite development for small satellites to deliver new capabilities. The UN Office for Outer Space Affairs reported thatspace-based services from navigation- and earth observation satellites are beneficial to 40% of UN ́s Sustainable Development Goals, which are important motivational factors for new research areas. Norway has strong national needs for maritime surveillance, forest monitoring and other types of land coverage monitoring, and has proven that even small satellites may service these needs through the AISSat- and NORSat-series. At CENSSS, we will build on this knowledge and expand our knowledge through research and development with close cooperation with our partners.

 

CENSSS will develop new exploitation models, application domains and services from New-Space Earth Observation satel- lites. For this, CENSSS will also investigate and explore data fom available satellites. New-Space technologies makes it possible to develop, manufacture and launch satel- lites in larger numbers and at lower costs. The large number of satellites will give a much shorter re-visit time for imaging a certain location on the Earth. It is expected that this new capability will generate a number of new products and make new applications possible.

 

Swarms of new satellites with electro optical imaging sensors and radar imaging sensors can collect a large volume of data and thereby generate high data rates that eventually will need to be sent down to Earth. There is a large momentum in Artificial Intelligence and Deep Learning that can be used to reduce the amount of data needed to be downlinked. Additionally, the use of Edge Computing, where intelligent processing and data reduction done onboard, can also reduce the need for a high data rate link.

Team

Stian Løvold (Work Package Leader)

Kristoffer Langstad (PhD Candidate)

TBA (PhD Candidate)

TBA (PostDoc)

TBA (PostDoc)

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