SBIR/STTR Award attributes
Our proposed innovation is a two-component system that, combined, constitutes our Toolkit for UAM Communications Management, or TUCM. The first component represents a deep dive into computing the path loss (or equivalently, the signal strength) for AAM flights given the link distance, carrier frequency, surface reflection coefficient, and relative path loss difference between a line-of-sight wave and a multipath wave. Our proposed path loss prediction tool is a machine learning (ML) model that is trained using data from ray tracing software. This first component builds on work that Mosaic ATM has already completed regarding path loss estimation in a UTM environment; the innovation here is to extend it to a higher-altitude UAM environment.The second component of TUCM is a blueprint that will help the wider aviation community collaboratively develop and mature the architecture of a robust UAM/AAM communications infrastructure. This more general, but comprehensive, view will be useful from UML-4 through UML-6. We envision that such a system would provide ground communication, air-to-air communication, and satellite communication. The combination of these technologies will ensure continuous coverage and robust reconfiguration if the communication link is severed, for example, by providing an ad hoc airborne network that can be rapidly reconfigured.
