Systems intending to achieve any level of space situational awareness inevitably require operator interfaces that enable the operation of sensors and the utilization of sensor provided data. As sensors are frequently owned and operated by other agencies, significant modification of the individual sensor capabilities may be beyond the reach of the space situational awareness system designer. The utilization of the sensor data however is not limited by anything except the ability of the space situational awareness system designer to innovate. The mission of the Architecture Driven Systems Laboratory (ADSL) at the University of Arizona’s Systems and Industrial Engineering department is to explore such innovations in all aspects of system architecture- especially the operator interfaces. The ADSL has developed an initial operating capability encapsulated in the System Architecture Synthesis and Analysis Framework (SASAF). The SASAF’s Operations Phase capabilities include separate instantiable tools modeling operation of sensors (i.e., the Sensor Tasking Tool), and utilization of sensor data (i.e. The Integrated Sensor Viewer). The Sensor Tasking Tool provides little opportunity for innovation because it is limited by the available sensors. However, the Integrated Sensor Viewer (ISV) provides substantial opportunities for innovation to help operators visualize and understand Resident Space Object (RSO) ephemeris data. The ISV implements a dynamic ontology developed within the software Unity correlates RSO data to commercial SSA company LeoLabs data retrieval API, allowing users to access additional information in-situ, without disrupting their sensory immersion and situational awareness. Product documentation generated in the ADSL allow stakeholders to better understand the final product.
CITATION STYLE
Kirshner, M., & Gross, D. C. (2019). Human-Computer Interaction for Space Situational Awareness (SSA): Towards the SSA Integrated Sensor Viewer (ISV). In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11575 LNCS, pp. 504–515). Springer Verlag. https://doi.org/10.1007/978-3-030-21565-1_34
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