LAUSR

The quality of unmanned aerial vehicle flight control and management system (UAV FCMS) software is crucial to guaranteeing the quality of UAVs. Software requirement elicitation (SRE) is an important part of the UAV FCMS software development process. However, this activity suffers from ambiguity, heterogeneity and incompleteness; furthermore, because the use of UAVs is closely related to their geographic environment, geographic environment factors must be fully considered when conducting UAV FCMS SRE activity. In the knowledge engineering community, an ontology is an explicit specification of a conceptualization. Introducing the ontology method into the SRE process is an effective way to solve the above problems. This paper creates a UAV FCMS SRE ontology (SREO) based on domain knowledge and empirical data, as well as a geo-ontology based on geographic information metadata. Then, the paper integrates the above two ontologies into a new ontology. The goal of ontology integration is to analyze ontology concepts by adopting a hybrid ontology mapping method. The specific process analyzes the semantic similarities between the concepts of two ontologies and then decides whether to use a description logic (DL) strategy based on the analysis results. When the corresponding conditions are satisfied, the DL strategy is used to perform both direct and transitive reasoning for the relationships to achieve the ontology mapping, and the ontology integration is eventually implemented. Finally, this paper uses a criteria-based ontology evaluation approach to evaluate the quality of the newly integrated ontology. The evaluation results show that the UAV FCMS SREO considering geographic environment factors exhibits high quality. Further engineering practices also show that the SRE activities and the generated software requirement specifications (SRSs) exhibit a large increase in quality. Through the above activities, improvements to both the quality and reliability of UAV FCMS software can be achieved.