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GNSS SATELLITE VISIBILITY ANALYSIS BASED ON 3D SPATIAL INFORMATION IN URBAN AREAS

机译:基于城市地区3D空间信息的GNSS卫星可见性分析

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Global Navigation Satellite System (GNSS) is a matured modern technique for spatial data acquisition. Its performance has a great correlation with GNSS receiver position. However, high-density building in urban areas causes signal obstructions and thus hinders GNSS’s serviceability. Consequently, GNSS positioning is weakened in urban areas, so deriving proper improvement resolutions is a necessity. Because topographic effects are considered the main factor that directly block signal transmission between satellites and receivers, this study integrated aerial borne LiDAR point clouds and a 2D building boundary map to provide reliable 3D spatial information to analyze topographic effects. Using such vector data not only reflected high-quality GNSS satellite visibility calculations, but also significantly reduced data amount and processing time. A signal obstruction analysis technique and optimized computational algorithm were also introduced. In conclusion, this paper proposes using superimposed column method to analyze GNSS receivers’ surrounding environments and thus improve GNSS satellite visibility predictions in an efficient and reliable manner.
机译:全球导航卫星系统(GNSS)是一种用于空间数据采集的成熟现代技术。其性能与GNSS接收器位置具有很大的相关性。然而,城市地区的高密度建筑导致信号障碍物,因此阻碍了GNSS的可维护性。因此,城市地区削弱了GNSS定位,因此获得了适当的改进决议是必需品。因为地形效应被认为是直接阻止卫星和接收器之间的信号传输的主要因素,所以这项研究集成了空中传播激光雷云和2D建筑边界地图,提供了可靠的3D空间信息来分析地形效果。使用这种矢量数据不仅反映了高质量的GNSS卫星可见性计算,而且显着降低了数据量和处理时间。还介绍了一种信号阻塞分析技术和优化的计算算法。总之,本文建议使用叠加的列方法来分析GNSS接收器的周边环境,从而以有效可靠的方式改进GNSS卫星可见性预测。

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