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Earth observation satellite programs are currently facing, for some applications, the need to deliver hourly revisit times, sub-kilometric spatial resolutions and near-real-time data access times. These stringent requirements, combined with the consolidation of small-satellite platforms and novel distributed architecture approaches, are stressing the need to study the design of new, heterogeneous and heavily networked satellite systems that can potentially replace or complement traditional space assets. In this context, this paper presents partial results from ONION, a research project devoted to studying distributed satellite systems and their architecting characteristics. A design-oriented framework that allows selecting optimal architectures for a given user needs is presented in this paper. The framework has been used in the study of a strategic use-case and its results are hereby presented. From an initial design space of 5586 potential architectures, the framework has been able to pre-select 28 candidate designs by an exhaustive analysis of their performance and by quantifying their quality attributes. This very

An optimal payload selection conducted in the frame of the H2020 ONION project (id 687490) is presented based on the ability to cover the observation needs of the Copernicus system in the time period 2020–2030. Payload selection is constrained by the variables that can be measured, the power consumption, and weight of the instrument, and the required accuracy and spatial resolution (horizontal or vertical). It involved 20 measurements with observation gaps according to the user requirements that were detected in the top 10 use cases in the scope of Copernicus space infrastructure, 9 potential applied technologies, and 39 available commercial platforms. Additional Earth Observation (EO) infrastructures are proposed to reduce measurements gaps, based on a weighting system that assigned high relevance for measurements associated to Marine for Weather Forecast over Polar Regions. This study concludes with a rank and mapping of the potential technologies and the suitable commercial platforms to cover most of the requirements of the top ten use cases, analyzing the Marine for Weather Forecast, Sea Ice Monitoring, Fishing Pressure, and Agriculture and Forestry: Hydric stress as the priority use cases.

The DEIMOS-2 mission, launched in June 2014 and currently carrying out routine operations, is aimed at operating an agile small satellite for high-resolution Earth Observation applications. The spacecraft can be steered to accurately point the payload up to 45° off-nadir. The platform agility makes mission planning a complex optimization problem, which is cumbersome for human operators. Automation emerges as a key enabler for the mission planning and exploitation process. This paper presents the "Capacity Analysis and Mission Planning Tool" developed by DEIMOS to produce feasible acquisition sequences from a set of user areas of interest. By feasible, we mean they do not overlap and they fulfil the platform constraints: attitude manoeuvring agility and stability requirements, on-board memory and downlink, power production and battery capacity. Besides the significant workflow enhancement obtained by the full automation of mission planning, the tool is also able to optimize the mission return by repeating the scheduling exercise and selecting the best-performing mission timeline. In addition, the tool can simulate the execution of user-defined sequences of spacecraft operations (i.e., mission timelines), thanks to a high-fidelity system simulator, and detect any possible resource conflict in terms of agility, power and memory.