The ganged phased array radar risk mitigation system: integrating weather effects

Technology advances have resulted in rapid developments in unmanned aircraft systems (UASs). The widespread utilization of those systems, however, is limited by the inability of these systems to “sense and avoid” other aircraft in uncontrolled air space. As a means for providing this capability, researchers at the UND John D. Odegard School of Aerospace Sciences are developing a Ganged Phased Array Radar Risk Mitigation System (GPARS-RMS), the purpose of which is to provide information that enables the deconfliction of both manned and unmanned aircraft within a given airspace.

As part of the development of GPARS-RMS, weather impacts are being considered. Weather can impact UAS operations in many ways, such as direct damage to unmanned aircraft (UA) from thunderstorms (lightning, hail, turbulence), loss of UA performance due to icing, and inadvertent aircraft interactions owing to “unmanaged” electromagnetic propagation effects. To mitigate such effects and thus enable weather-based risk mitigation within the GPAR-RMS, efforts are being directed towards enhancing and extending data assimilation capabilities within the Weather Research and Forecasting model. Specifically, data from the phased array radars used within the GPAR-RMS are to be assimilated, along with conventional data sources, within a high-temporal frequency cycled assimilation-forecast framework. The output of this system will be used in tandem with raw observations to identify weather hazards (e.g., thunderstorms) within the airspace sampled by the GPAR-RMS such that UA can avoid all potential hazards (including aircraft). The GPAR-RMS visualization system displays detected hazards and integrates these hazards into a risk level monitor that indicates the instantaneous risk level associated with current UA operations.

In addition to direct impacts of weather, potential impacts of the presence of anomalous electromagnetic propagation conditions are included. Such conditions pose a significant risk in that the resulting propagation could inadvertently cause an aircraft to not be sensed due to detection holes arising from the trapping or ducting of electromagnetic energy. Output from the data assimilation system is used to create refractive index profiles to determine actual propagation conditions.

This presentation will describe the GPAR-RMS, the data assimilation system being developed within the GPAR-RMS, and the utilization of weather information within the GPAR-RMS to mitigate risks associated with UA operations. Development, testing, opportunities, and challenges will be discussed.