In parallel with the decrease in cost, size and weight of Unmanned Aerial Vehicles (UAVs) and the increase of their flight autonomy, many commercial applications are rapidly arising. Most of those applications rely on a communications system between a terrestrial base station and the UAV. Due to the UAV movement, time-variant channel models are required. In this article, we propose a geometrical model for the channel Multipath Components (MPCs) evolution with the UAV flight that supports MPCs that are born and die in several occasions due to blockages. Based on this model, the novel Geometry-Based Spatial-Consistent MPC Tracking Method (GSTM) is proposed and its performance on channel MPCs tracking was shown both by simulations and by an Air-to-Ground (A2G) low-height UAV measurement campaign. The GSTM also provides the parameters of a geometrical model of the evolution of the main MPCs of the channel, which allows to identify the scatterers that lead to the MPCs and greatly contributes to the understanding of the propagation mechanisms in A2G environments. The correctness of the MPC tracking is proven to be higher than 90% and the results show that the model obtained by the GSTM includes more than 95% of the received power.

中文翻译：

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基于几何的MPC随行无人机通道跟踪与建模算法

随着无人机的成本，尺寸和重量的减少以及其飞行自主性的增加，许多商业应用正在迅速兴起。这些应用中的大多数都依赖于地面基站和UAV之间的通信系统。由于无人机的运动，需要时变通道模型。在本文中，我们为随无人机飞行的通道多路径组件（MPC）演化提出了一种几何模型，该模型支持因阻塞而在多种情况下出生和死亡的MPC。在此模型的基础上，提出了一种新颖的基于几何的空间一致性MPC跟踪方法（GSTM），并通过仿真和空对地（A2G）低空无人机测量活动展示了其在通道MPC跟踪上的性能。GSTM还提供了通道主要MPC演变的几何模型的参数，从而可以识别导致MPC的散射体，并极大地有助于理解A2G环境中的传播机制。事实证明，MPC跟踪的正确性高于90％，结果表明，通过GSTM获得的模型包含超过95％的接收功率。