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A communication approach for aerial surveillance of long linear infrastructures in non-urban terrain

机译:一种用于非城市地形中的长线性基础设施的空中监视的通信方法

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3-D modeling of aerial wireless coverage is an important requirement for many an applications of UAVs. Typically such model is used in communication-aware path planning of the vehicle. When the surveillance area is vast, such as that of long linear utility infrastructures e.g. power grids, oil and gas pipelines, railway corridors etc., signal coverage is quite sparse due to lack of transmitters in rural/forested terrain. On the other hand, maximal connectivity so as to robustly transmit huge volumes of sensed data in downlink is highly required. However, coverage models for vast areas, especially in remote rural surroundings having complex terrain, are not publicly known, thus inhibiting mission planning for an important class of UAV applications. In this paper, we have tried to address this requirement by establishing such a coverage model. The model is based on a 3-D mesh of sampling locations, over which a sparse set of signal strength measurements are available using pilot flights. From the sparse set, we use heuristics of distance-weighted averaging to closely approximate and predict signal strength measurements at other grid points. We propose a novel metric of representative distance, which leads to approximation error become as less as 5%. The solution holds the promise of being scalable to big grid sizes, as is demonstrated by the simulation results. We believe that this model will form an important stepping stone towards evolution of more robust models, which in turn are needed to enable many an important civilian applications of UAV as a sensing platform.
机译:空中无线覆盖的3-D建模是许多无人机应用的重要要求。通常,这种模型用于车辆的通信感知路径规划中。当监视区域很大时,例如线性公用事业基础设施较长的区域电网,石油和天然气管道,铁路走廊等,由于农村/森林地带缺少发射器,信号覆盖范围非常稀疏。另一方面,迫切需要最大的连通性以在下行链路中稳健地传输大量的感测数据。但是,尚未公开广域的覆盖模型,尤其是在地形复杂的偏远乡村环境中,因此阻碍了针对一类重要的无人机应用的任务计划。在本文中,我们试图通过建立这种覆盖模型来满足这一要求。该模型基于采样位置的3-D网格,在该网格上,可以使用飞行员的飞行来获得一组稀疏的信号强度测量值。从稀疏集合中,我们使用距离加权平均的启发法来近似估计和预测其他网格点处的信号强度测量。我们提出了一种新颖的代表距离度量,它导致近似误差小于5%。仿真结果表明,该解决方案有望扩展到较大的网格尺寸。我们相信,该模型将成为迈向更健壮模型发展的重要踏脚石,而反过来又需要这些模型,以使许多重要的民用无人机应用成为传感平台。

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