Unmanned Aerial Vehicle Identification Success Probability with LoRa Communication Approach

Abstract

Identifying unmanned aerial vehicles(UAVs) has become an important task as the number of UAVs used for various purposes increases. The importance of UAV identification is increasingly emphasized as news of UAV attacks on critical national facilities has been heard. In order to respond effectively to UAV movement, detection, identification, and neutralization phases are expected to be required. Among these, in order to identify UAVs wirelessly, it is necessary to select a wireless communication method suitable for an UAV identification environment. Basically, because UAVs are likely to be high and far from ground-based identifiers, and the UAV’s batteries are limited, it is necessary to consider LPWA-based communication. In this paper, LoRa’s RF system parameters and various propagation models are used to derive the UAV identification success probability using LoRa technology, a representative Low Power Wide Area(LPWA) communication method and we present the probability of UAV identification success with distance by propagation model and spreading factor. In addition, the relationship between the speed of the UAV and the spreading factor and bandwidth of the LoRa system capable of drone identification is also described.