Modeling and Simulation of Ground Based Radar Surveillance Solutions for Unmanned Aircraft System Sense and Avoid

Abstract

Radar systems provide surveillance information for air traffic management (ATM), border protection and national security. Radar wave propagation is affected by atmospheric and environmental conditions, terrain, and land coverage. Performance analysis of primary surveillance radar systems is critical for enabling routine Unmanned Aircraft System (UAS) access to the National Airspace System (NAS). The safe operation of UAS in the NAS necessitates a capability to sense and avoid other airborne objects. One solution is a Ground Based Sense and Avoid (GBSAA) concept, which fuses radar data in a specially tuned tracking system and provides traffic information to a ground observer and pilot. In this paper, we will present a modeling and simulation approach for assessing site-specific radar detection performance and apply the results to the GBSAA application. High fidelity primary surveillance radar performance and tracking system models enable simulation studies with the objective of determining target probability of detection and distributions of expected track initiation times across the surveillance volume. These models take into account target characteristics, site-specific radar performance, and tracking system filtering and initiation logic. This information will help in the development of a GBSAA concept of operation, mission planning, and will ultimately define where UAS can operate with sufficient surveillance coverage to meet sense and avoid functional requirements. In addition to this application, the radar modeling and simulation techniques discussed in this paper can be extended to evaluate the impact of disruptive technologies and structures such as wind farms, large solar arrays, and nearby buildings and towers.