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To better understand the Earth environment and climate change, to mitigate its effects and to provide emergency services, ensuring civil security, future European Earth observation (EO) infrastructures will heavily rely on operational satellite missions. To ensure continuous and timely provision of spaceborne Earth-observation data, these missions will be characterized by high temporal resolution, high availability, low latency and enhanced synergies between different observation products. These goals will likely be achieved by deploying multi-asset satellite systems, such as constellations. In order to design robustly the architecture of these EO systems, given a certain set of observational requirements, OHB System AG has developed a methodology and the associated tools, to optimize the multi-asset system, taking into account physical and technical constraints. In general, for a specific repeating ground track Sun-synchronous orbit and a given number of spacecraft, one (or more) optimal orbital configuration(s) (i.e. anomaly separation on the same orbit) exists that allows achieving full global coverage in a prescribed number of days and minimizes the required swath size. The objective of this paper is to define the optimization model associated to this problem: the swath size is a key design parameter, most of the time constrained by mission requirements and/or technology readiness. Both Non Linear Programming and Mixed Integer Linear Programming are proposed to solve the optimization problem and are investigated in the paper: the formulation is derived and advantages and drawbacks of each are detailed. Finally, the two formulations are tested with different software and on multiple study cases: the effectiveness of the developed methodology is supported by application and validation examples.

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