Performance Analysis of RIS-Assisted RF-Based Detection of Unauthorized UAVs

In this paper, the problem of unauthorized drone detection is considered. In particular, we propose a novel RF-based UAV detection technique aided by reconfigurable intelligent surfaces (RISs) considering realistic air-to-ground (A2G) channel conditions under Rician fading channels. Furthermore, we develop an analytical framework that provides the optimal phase shifts of the RISs and closed-form expressions for the detection probabilities. Additionally, the impact of the RISs placement is investigated considering the worst-case scenario in which we have a minimum detection probability. Finally, the minimum number of reflecting elements per RIS required in the case of blocked direct line-of-sight (LoS) is derived to outperform the LoS conditions without the assistance of RISs. Monte Carlo simulations corroborate and confirm the accuracy of the derived expressions under the aforementioned channel conditions and we demonstrate the average detection probability given randomly distributed RISs. Our results have shown that an overall accuracy of 0.99 can be achieved under the scenarios when active RISs are utilized along with an existing direct LoS link.