Abstract: A component-based system and method for rapidly generating artificial intelligence-enhanced real-time, multi-dimensional gridded aerial object classification and trajectory (state and orbital state vector) forecasts utilizing digital radar signals data collected at high rates of volume and velocity. The system performs data storage, retrieval, manipulation, communication, processing, and end user application tasks for accurate aerial object classification and vector forecasts. The data component serves as a data cache to store, retrieve, and manipulate data utilizing a plurality of functions under conditions of variable internet connectivity. The processing component includes an artificial intelligence machine learning component and logic for manipulating the data to generate gridded projections that are arrayed spatially and temporally.

Abstract: A component-based system and method is provided for generating and processing multi-dimensional gridded mesoscale meteorological projections. In embodiments, the system includes four integrated processes for data storage, retrieval, manipulation, communication, processing, and end user application tasks. Two or more components may interface for performing tasks. A data component stores, retrieves, and manipulates data utilizing functions under conditions of variable internet and non-internet connectivity. A communications component transmits and receives data to/from the data component for manipulation by the processing component. The processing component includes an artificial intelligence machine learning component and logic for manipulating the data to generate gridded mesoscale meteorological projections arrayed spatially and temporally.