Abstract
Autonomous satellite clusters are known for having such merits as low cost, high performance, and high additivity. However, certain limitations exist in the process of efficiently generating run-time task configuration for multimission satellites in regard to the support for self-adaptation of the satellite cluster system. To address these limitations, this paper outlines an ontology-based self-synthesis method for task configuration in the context of satellite clusters. The satellite cluster ontology is presented as the foundation of the method, which provides both semantical and factual knowledge base about the satellite cluster and its working environment. Then a four-step workflow illustrates how the task configuration generation mechanism creates the solution space tree and finds the optimal solution of task configuration by deducing constraints from ontological knowledge and solving the constrained optimization problem. Based on the ontology model of the satellite cluster, a task configuration generation mechanism using SPARQL query is provided to query task-related knowledge step by step. Finally, the optimal task configuration is calculated from the constrained optimization problem. This new architecture is evaluated through a case study of an image acquisition mission with a three-satellite cluster and is found to be effective for obtaining task configuration and reconfiguration during run time.
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