This activity developed high-performance data compression software with embedded data analysis features for radio-frequency, multi-band images and video. It offers excellent compression ratios and quality levels with very small computing requirements, which even allow for real-time operation on modest processors. Tests on data from ESA's OPS-SAT satellite reveal image ratios over 1:10 with excellent visual quality, and radio-frequency ratios over 1:3 with nearly identical spectrograms thanks to a smart lossy approach.

Radio Frequency Interference (RFI) impact heavily on a wide variety of space applications/services belonging to different areas, such as Telecommunications, Navigation and Earth Observation. Despite the huge number of interfering signal types, a preliminary classification of Interference may be performed according to the nature of interfering sources: - Intentional interferences. The transmitting events are deliberately performed for attacking other systems (e.g., jamming, spoofing, etc.); - Unintentional interferences.

Many use cases for insight generated in orbit require the integration and calibration of raw data from multiple instruments and vantage-points – a future vision sometimes referred to as ‘hybrid observation’. Such a capability would be a foundational requirement in the processing chain for rapid follow-up observations especially when we need to estimate quantitative variables (e.g. soil moisture or water pollutants).

‘STARCOP’ is an initiative to use machine learning and multiple satellites with diverse detection capabilities to quickly detect methane leaks and send notifications in near real-time. In this project Trillium Technologies developed machine learning models to automatically detect methane in hyperspectral and multispectral imagery. Their hyperspectral model (HyperSTARCOP) is able to capture more than 90% of plumes in test data while reducing the false positive rate by 39% when compared to state-of-the-art models.

The possibility to acquire and track signals for which the PRN code is not public (e.g. as for Galileo Public Regulated Service or any other non-public GNSS service) is of high interest in order to be able to assess, with real field signal, new acquisition and tracking techniques that otherwise can only be assessed with a full GNSS receiver with access to those PRN codes. In this context, the recovery of the unknown PRN codes from low-noise signal recordings (e.g.

The objective of the MARLISAT project was to further develop marine plastic monitoring through the use of multiple satellite technologies. In effect, the intention was to use satellite technology to detect marine litter, track it and forecast its pathways.

Four satellite technologies were combined:

In the ocean, transport and mixing processes tend to disperse matter in suspension over wide spatial (~100 km) and long temporal (~month) scales. Fronts appear at the boundary between water masses with different properties and are caused by diverse oceanic features and processes, including bottom topography. Frontal structures include tidal mixing fronts, shelf-break fronts, upwelling fronts, estuarine fronts, plume fronts, fronts generated by convergence or divergence of water masses, and frontal eddies (Acha et al. 2015; Largier 1993).

Development of instruments and algorithms for remote sensing of plastics need standardised global in-situ observations. Compared to aquatic environments, dry shores are more accessible to frequent in situ observations. As part of the HyperDrone project, funded by the Discovery Element of the European Space Agency’s Basic Activities, we aimed to develop a standardised indicator for in-situ radiometric detection of plastic debris with the view to be deployed globally on different platforms.

This project is conceived at analysing a secured communication link between a space-based system and a maritime system. The final goal is to serve autonomous navigation vessels, with a possible extension to other smart commercial maritime services and to favour the process towards a highly and full digitalisation of the Port system. The autonomous ship is here considered from an operating point of view, although quite simple and with the purpose of understanding the impact on the telecommunication system. The initial focus is on three possible telecommunication solutions:

The Ka-band frequency (35 GHz) is becoming increasingly attractive for spaceborne remote sensing applications. Unlike other radar bands, the Ka-band enables the development of compact high resolution interferometric instruments and embarking the payloads on a single platform. This creates unique new opportunities in Earth observation science and civil security applications, for instance in monitoring the changing cryosphere, generating high resolution maps of ocean currents and ship and vehicle detection.