SAVOIR has produced a set of generic specification under the form of documents, based on some physical architecture of equipment that was state of the art at that time. The new functional model based approach is more based on functional chains and models. It is expected that modelling the SAVOIR avionics architecture and generic specification using the MBSE techniques, in particular Arcadia method and Capella tool, will allow to have an innovative standpoint on the SAVOIR standardisation.

This activity is intended to investigate the Grazing Angle (GA) Carrier Phase Altimetry (CaPA) using signals transmitted by the Global Navigation Satellite Systems (GNSS). The CaPA technique requires that the electromagnetic signal reflects coherently rather than in a diffuse regime. The hypothesis is that GA geometries enhance the likelihood of coherence scattering. It was also hypothesized that the combination of signals at slightly different frequency bands could expand the coherence conditions (widelane techniques, WL).

The goal of the project was to develop a service as a product to simplify fitting DNN (Deep Learning Neural Networks) in on board HW to make better use of AI on space missions The role of the service is to support data processing engineers in reducing HW resources requirement of powerful DNN for image analysis to be executed onboard. 

The main objective of this activity was to develop and demonstrate new techniques which are expected to improve the current state-of-the-art Space Weather forecasting techniques and products related to Space Weather effects for Positioning, Navigation and Timing (PNT) systems in the Arctic, with particular attention to the Greenland area. For this purpose, the activity investigated and tested innovative methods for monitoring and predicting Space Weather impacts on PNT in interested area.

“Remote Sensing for Marine Litter - RESMALI” has identified the ideal parameters to study marine litter (ML) from space, including spectral bands with affordable signal-to-noise ratio (SNR) at top-of-atmosphere (TOA) level, in a range of wavelengths from visible to SWIR. To continue this path towards a dedicated mission, performance assessment against simulated real-case scenarios of ML is key. We want to build a simulator to estimate ML signal at TOA from a set of scenarios representing the various applications already targeted by the community (e.g.

Space system engineering is a complex activity, spanning multiple phases and involving different stakeholders using a variety of engineering approaches and tools. ESA has been investing in Model-Based System Engineering (MBSE) research for many years, developing different MBSE frameworks and Domain Specific Tools (DSTs). Recently, a broader need has been recognized to focus the MBSE efforts on semantic interoperability and associated model integration.

There is growing global concern over the chemical, biological and ecological impact of marine plastic pollution. Every year many millions of tons of plastic enter the global oceans but where it goes remains largely unknown. Remote sensing has the potential to provide long-term, global monitoring but for plastics in the ocean it is still in early stages.

With the increased frequency of shipping activities, such as tourism and freight’s transport, navigation safety has become a major concern, especially when human casualties, environmental issues and economic losses are considered. Even if new technologies have already supplied aids to pilots for the navigation risk reduction, the International Maritime Organization (IMO) reports that the majority of accidents could have been avoided by providing suitable input to the navigation decision-making process.

The main objective of the ELMASAT study was to brint into Capella the means to calculate the availability of a satellite system and provide extra facilities for trade-off analysis. As an example of application, an assesment of SEE detection and mitigation strategies was performed with respect to availability objectives.

The BIOINSPACED project was initiated to find bio-inspired solutions for space debris removal because the identification, orbital alignment, capture and removal of uncooperative bodies in space is incredibly complex and no fully functioning method is available to date. Biology and its evolved mechanisms often provide specialized concepts that show great transferability to technical systems.