Task prioritization on phased-array radar scheduler for adaptive weather sensing

More frequent observations of fast evolving weather phenomena can help with increasing the warning lead-time and improving forecasts. The recently installed phased array radar (PAR) at the National Weather Radar Testbed (NWRT) in Norman, Oklahoma is the first phased array radar system in the nation dedicated to weather radar research and can electronically steer the beam in both azimuth and elevation. Thus, the PAR has the potential for adaptive sensing, that is, to dynamically and interactively adapt its operating parameters according to the environment of interest. The decision of how to allocate PAR resources for competing tasks such as weather surveillance and tracking of multiple storm cells is a scheduling problem. We developed an adaptive scheduling algorithm based on the concept of Time Balance. As a result, weather surveillance and tracking of multiple storm cells, can be organized in the most advantageous manner. In this work, the prioritization procedure is based on adaptive fuzzy logic, which assigns priorities to multiple weather surveillance and storm tracking tasks according to their urgency and importance. Furthermore, task prioritization and Time Balance scheduling work together to provide the best allocation of PAR resources.