Earth orbiting support systems for commercial low earth orbit data relay: assessing architectures through tradespace exploration

As small satellites and Sun Synchronous Earth Observation systems are assuming an increased role in nowadays space activities, including commercial investments, it is of interest to assess how infrastructures could be developed to support the development of such systems and other spacecraft that could benefit from having a data relay service in Low Earth Orbit (LEO), as opposed to traditional Geostationary relays. This paper presents a tradespace exploration study of the architecture of such LEO commercial satellite data relay systems, here defined as Earth Orbiting Support Systems (EOSS). The paper proposes a methodology to formulate architectural decisions for EOSS constellations, and enumerate the corresponding tradespace of feasible architectures. Evaluation metrics are proposed to measure benefits and costs of architectures; lastly, a multicriteria Pareto criterion is used to downselect optimal architectures for subsequent analysis. The methodology is applied to two case studies for a set of 30 and 100 customer-spacecraft respectively, representing potential markets for LEO services in Exploration, Earth Observation, Science, and CubeSats. Pareto analysis shows how increased performance of the constellation is always achieved by an increased node size, as measured by the gain of the communications antenna mounted on EOSS spacecraft. On the other hand, nonlinear trends in optimal orbital altitude, number of satellites per plane, and number of orbital planes, are found in both cases. An upward trend in individual node memory capacity is found, although never exceeding 256 Gbits of onboard memory for both cases that have been considered, assuming the availability of a polar ground station for EOSS data downlink. System architects can use the proposed methodology to identify optimal EOSS constellations for a given service pricing strategy and customer target, thus identifying alternatives for selection by decision makers.