The project demonstrates a proof-of-concept of a next generation bio-inspired morphing wing inspired by academic research of the Peregrine Falcon morphology. Asymmetric span morphing has previously been demonstrated for UAV roll control via in-plane partial span change. This design has full bird-like span change and a unique out-of-plane modality. This offers novel drag reduction characteristics when made to form an airflow channel in conjunction with a fixed surface such as the fuselage, in “cupped wing” flight.

While AI technologies have shown promise in various applications in the space industry, their adoption within spacecraft flight software has yet to happen in a significant manner. This is due to a number of factors, including the relatively low computing power available onboard traditional spacecraft, the long development process required in the industry and the lack of opportunities for in-orbit demonstrations. In ESA's OPS-SAT satellite, Airbus teams identified a unique opportunity to quickly test promising algorithms in orbit as the industry seeks to resolve the issues listed above.

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.

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).

Currently, GNSS is the backbone of most Position, Navigation and Timing (PNT) solutions, in providing 24/7 continuous, all-weather, global coverage to an unlimited number of receiver-equipped users. There is an increasing dependency on the availability and reliability of GNSS. However, GNSS is widely known to be vulnerable to an evolving range of threats (natural and man-made, unintentional and deliberate).

This report documents our research and proposal for the “Design of a Scalable Framework of Lunar Habitats – an activity funded by the Discovery element in the European Space Agency as part of their OSIP (Open Space Innovation Platform) Off-Earth Manufacturing and Construction Campaign.