7 October 2014 Knowledge-intensive global optimization of Earth observing system architectures: a climate-centric case study
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Abstract
Requirements from the different disciplines of the Earth sciences on satellite missions have become considerably more stringent in the past decade, while budgets in space organizations have not increased to support the implementation of new systems meeting these requirements. At the same time, new technologies such as optical communications, electrical propulsion, nanosatellite technology, and new commercial agents and models such as hosted payloads are now available. The technical and programmatic environment is thus ideal to conduct architectural studies that look with renewed breadth and adequate depth to the myriad of new possible architectures for Earth Observing Systems. Such studies are challenging tasks, since they require formidable amounts of data and expert knowledge in order to be conducted. Indeed, trade-offs between hundreds or thousands of requirements from different disciplines need to be considered, and millions of combinations of instrument technologies and orbits are possible. This paper presents a framework and tool to support the exploration of such large architectural tradespaces. The framework can be seen as a model-based, executable science traceability matrix that can be used to compare the relative value of millions of different possible architectures. It is demonstrated with an operational climate-centric case study. Ultimately, this framework can be used to assess opportunities for international collaboration and look at architectures for a global Earth observing system, including space, air, and ground assets.
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D. Selva, D. Selva, } "Knowledge-intensive global optimization of Earth observing system architectures: a climate-centric case study", Proc. SPIE 9241, Sensors, Systems, and Next-Generation Satellites XVIII, 92411S (7 October 2014); doi: 10.1117/12.2067558; https://doi.org/10.1117/12.2067558
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