NASA selects Mosaic ATM to develop signal strength toolkit for AAM aircraft
LEESBURG, Va., - The National Aeronautics and Space Administration (NASA) needed a new solution to utilize deep learning to predict signal strength...
LEESBURG, Va., - The National Aeronautics and Space Administration (NASA) needed a new solution to utilize deep learning to predict signal strength at low altitude for an advanced air mobility (AAM) aircraft. They selected Mosaic ATM in Leesburg, Virginia, to develop that solution. The machine learning system is trained using high-fidelity physics-based simulated data and actual data recorded from test flights. Using a combination of convolutional neural networks and deep learning systems, the accuracy of the estimation will be high, Mosiac says, with a speed that is about ten times faster than current physics-based algorithms, and will be applied to the low-altitude UAM communications system.