UAV-aided Wireless Node Localization Using Hybrid Radio Channel Models

• URL: http://arxiv.org/abs/2205.03327v1
• Date: Fri, 6 May 2022 16:04:42 GMT
• Title: UAV-aided Wireless Node Localization Using Hybrid Radio Channel Models
• Authors: Omid Esrafilian, Rajeev Gangula, and David Gesbert
• Abstract summary: We treat UAV-user link channel model parameters and antenna radiation pattern of the UAV as unknowns that need to be estimated. A hybrid channel model is proposed that consists of a traditional path loss model combined with a neural network approximating the UAV antenna gain function. We then employ the particle swarm optimization technique which utilizes the learned hybrid channel model along with a 3D map of the environment to accurately localize the ground users.
• Score: 19.374861475180712
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: This paper considers the problem of ground user localization based on received signal strength (RSS) measurements obtained by an unmanned aerial vehicle (UAV). We treat UAV-user link channel model parameters and antenna radiation pattern of the UAV as unknowns that need to be estimated. A hybrid channel model is proposed that consists of a traditional path loss model combined with a neural network approximating the UAV antenna gain function. With this model and a set of offline RSS measurements, the unknown parameters are estimated. We then employ the particle swarm optimization (PSO) technique which utilizes the learned hybrid channel model along with a 3D map of the environment to accurately localize the ground users. The performance of the developed algorithm is evaluated through simulations and also real-world experiments.

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