Background and justification:

The space industry and space agencies have been aware for quite some time of the interest and added value of model-based system engineering (MBSE) in streamlining the design, development, deployment and verification of space systems. There have been many initiatives during the past decades aiming at defining models and tools able to support the various needs of the system engineering process. MBSE is increasingly being used in operational projects and the next step is to use MBSE extensively throughout the system life cycle, across disciplines and throughout the supply chain.

Artificial intelligence will allow vast quantities of earth observation data to be analyzed. Image compression can both provide a performance boost and make systems more economical. However, most high-performance compression methods have been tuned to the human eye, rather than developed for machine vision, generating artefacts that although invisible limit the performance of advanced algorithms. Compression targeting AI and high radiometric accuracy applications is needed.

This activity aims to understand better the complete environmental impacts of space missions, filling the knowledge gaps from previous studies. This in turn allows identification of areas where impacts are concentrated (hotspots) in order to focus future attention for making improvements.

In an era of high resolution gravity field modelling the dominant error sources in spacecraft orbit determination are non-conservative spacecraft surface forces, such as: Solar Radiation Pressure, antenna thrust, Earth' albedo, thermal re-radiation, etc. The conventional approach to these problems is to use an empirical blind model which absorb all the forces but this approach introduces systematic errors and limit the prediction of the orbit. In the last years several wind-box model have appeared, developed based in GPS and Glonass official information, to overcome this limitation.

In an era of high resolution gravity field modelling the dominant error sources in spacecraft orbit determination are non-conservative spacecraft surface forces, such as: Solar Radiation Pressure, antenna thrust, Earth' albedo, thermal re-radiation, etc. The conventional approach to these problems is to use an empirical blind model which absorb all the forces but this approach introduces systematic errors and limit the prediction of the orbit. In the last years several wind-box model have appeared, developed based in GPS and Glonass official information, to overcome this limitation.

The ESA TASTE project is used to create and modify (among other things) Message Sequence Diagrams. But the editor tool for this is not at the technological level where it is useful in production, and where suppliers are able to do training and support programs. This study created a new implementation using state of the art software development design to create the foundation of the new TASTE applications.

The current redundancy approach is often intended to maintain or re-establish full functionality and performance capability in case of failure of a primary system or equipment. This naturally leads to build and carry system resources that may never be used in case the primary system works reliably throughout its operational life. On the other hand, alternative concepts exist which implement simply the capability of maintaining certain acceptable level of performance (i.e. graceful or acceptable degradation) in case the primary system fails.

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