A Toolkit for UAM Communications Management

Air/Ground (AG) communications (AG Comm) are well established for traditional National Airspace System participants, but for the Advanced Air Mobility (AAM) concept, the infrastructure, frequency bands, and related infrastructure build-outs are in their infancy. Initially, AAM pilots will be in the cockpit and AG Comm will use existing voice channels. However, for UAM Maturity Level 4 (UML-4) and onwards, vehicles are controlled by remote pilot. AG Comm will require higher bandwidths than AG Comm does today for transmitting video and reproducing the cockpit on the remote pilotrsquo;s workstation (a digital twin of the aircraft).TUCM targets this remote pilot concept, UML-4 and onwards. TUCM uses a combination of statistical and Machine Learning (ML) tools to estimate the signal strength as a vehicle traverses the airspace. The signal strength is a complicated function of direct line of sight, multipath interference due to reflections off the ground and nearby buildings, electromagnetic interference, and atmospheric effects. This problem is compounded by the movement of the vehicle.nbsp; The signal strength computations are then packaged into a marketable toolkit that can be inserted as a module into existing AAM management tools, AAM simulations, or used as a stand-alone tool for engineering and health checking of communication systems.nbsp; TUCMrsquo;s purpose is to increase the resiliency and reliability of AAM AG Comm.