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The main objective of the OMAR Mission Architecture study is to identify and trade-off different mission architectures, to provide different services on-orbit. For each of the relevant scenarios, this objective shall be achieved by defining the associated system functional analysis and by trading-off different architectures and concepts of operations. Furthermore, the impact of aspects such as: operational orbit, type of serviced satellites, services provided, different levels of autonomy, and any other relevant factors is to be assessed.

The aim of the LIFELINE project was to perform a feasibility study of a Relativistic Positioning System. Nowadays, all GNSS in operation are based on Newtonian physics and rely on global reference frames fixed to Earth. Relativistic effects are treated as deviations that need to be corrected. A practical RPS would consist, for example, in a constellation of satellites, each one broadcasting not only its General Relativity coordinates (proper times or other observables) at emission but also the coordinates that it receives from the other satellites.

The “Detection of Ocean Litter Plastics with Hyper-to-multispectral Infrared Neural Networks” (DOLPHINN) study explored a novel image processing technique to improve the use of space assets to map the distribution of plastic across the globe. The DOLPHINN project objective was to determine the feasibility of using a hyperspectral-to-multispectral association machine learning approach to improve the capability of space-based short wave infrared (SWIR) multispectral assets to detect, quantify, and track plastic litter in waters and on shorelines.

The main objectives of the project are to:
▪ Assess how plastic litter can be detected and quantified with current and future remote sensing tools;
▪ Develop adaptive indices insensible to biases induced by sunglint on satellite radiometric products and indicate the constraints of current satellite missions under various atmospheric and illumination conditions;