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The progress in wireless technology over the past decade led to the rapid adoption of unmanned aerial vehicles (UAVs) for various applications. As the interest in UAVs is accelerating, increased attention is paid to the reliability and resilience of UAV-based systems with respect to the collision avoidance. One of the ways to improve this aspect is to utilize the RADAR functionality. In this work, we consider a cellular network employed for communication jointly with RADAR operation. The critical parameter that affects the RADAR algorithm is the radar cross-section (RCS). Since the task of obtaining the RCS of a complex-shaped object is extremely challenging, we first propose a novel, accurate, and fast method of scattered field assessment. We further perform radio network planning for the cellular deployment, as well as link budget estimations for the RADAR system that co-exists with it. Under this system model, we carry out detailed Monte-Carlo simulations of the RADAR detection process to obtain reliable statistical results and answer the question of how the actual bistatic RCS model affects the detection algorithm. We then apply mathematical modeling based on stochastic geometry to estimate the collision probability without the need to simulate an extensive number of flight-hours. Our numerical results confirm the robustness to RCS pattern nulls, which is crucial for safety-centric applications such as collision avoidance.

Distributed Communication and Sensing System Co-Design for Improved UAV Network Resilience