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This paper considers the problem of ground user localization based onreceived signal strength (RSS) measurements obtained by an unmanned aerialvehicle (UAV). We treat UAV-user link channel model parameters and antennaradiation pattern of the UAV as unknowns that need to be estimated. A hybridchannel model is proposed that consists of a traditional path loss modelcombined with a neural network approximating the UAV antenna gain function.With this model and a set of offline RSS measurements, the unknown parametersare estimated. We then employ the particle swarm optimization (PSO) techniquewhich utilizes the learned hybrid channel model along with a 3D map of theenvironment to accurately localize the ground users. The performance of thedeveloped algorithm is evaluated through simulations and also real-worldexperiments.

UAV-aided Wireless Node Localization Using Hybrid Radio Channel Models