UAV mapping for multiple primary users localization

The unique features of unmanned aerial vehicles (UAVs) extend a large number of existing technologies into environments that are not suitable for on-site operations. Localization, a critical basis of many applications such as cognitive radio and first response networks, can benefit UAV technology as well. In such scenarios, an underinvestigated problem is the non-collaborative localization of multiple primary users (PUs). Therefore, this work proposes a data-driven multiple PU localization algorithm based on the angular and power measurements performed by a UAV equipped with an antenna array. The measured data firstly generate a score map, then a threshold and a hierarchical clustering method are applied to the score map to both detect the number of PUs and estimate their location. The performance of the algorithm is assessed by numerical results in terms of probability of detecting the number of PUs, and root-mean-square-error of position estimation. The proposed solution exhibit remarkable performance considering that the approach requires only the knowledge of the PUs frequency band.