论文标题
使用混合无线电通道模型的无人用无线节点定位
UAV-aided Wireless Node Localization Using Hybrid Radio Channel Models
论文作者
论文摘要
本文根据接收的信号强度（RSS）测量来考虑地面用户本地化的问题，该测量由无人机（UAV）获得。我们将无人机的链接通道模型参数和无人机的天线辐射模式视为需要估计的未知数。提出了一个混合通道模型，该模型由传统的路径损耗模型与近似UAV天线增益功能的神经网络相结合。使用此模型和一组离线RSS测量值，估计未知参数。然后，我们采用了粒子群优化（PSO）技术，该技术利用了学习的混合通道模型以及环境的3D地图来准确地定位地面用户。通过模拟和实际实验评估了开发算法的性能。
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.
