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Deep fusion of vector tracking GNSS receivers and a 3D city model for robust positioning in urban canyons with NLOS signals

机译:矢量跟踪GNSS接收器和3D城市模型的深度融合,可利用NLOS信号在城市峡谷中进行可靠定位

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摘要

In urban canyons, the GNSS satellite signals may travel an additional distance due to reflection and diffraction before reaching the receiver antenna. Where no direct path is available, this is called a non-line of- sight (NLOS) propagation and adds a positive bias to the geometric measured pseudorange. In this paper, we address the issue of GNSS positioning in harsh environments using constructively the NLOS signals. To exploit these biased signals, we compensate for the NLOS bias using a 3D GNSS simulation model of the environment. We use the 3D model as a priori information to characterize the additional NLOS bias. In this work, we propose a deep integration of the 3D model-based signal characterization into an advanced GNSS receiver architecture called vector tracking loops. The proposed architecture is a combination of a vector tracking receiver and a co-processor of external local information to correct the GNSS measurements. Obtained results with real GPS signals illustrates the effectiveness of this approach to improve the accuracy and reliability of the navigation solution in urban canyons.
机译:在城市峡谷中,由于反射和衍射,GNSS卫星信号在到达接收器天线之前可能会传播另外的距离。在没有直接路径可用的地方,这称为非视线(NLOS)传播,并向几何测量的伪距增加了正偏差。在本文中,我们通过建设性地使用NLOS信号解决了恶劣环境中GNSS定位的问题。为了利用这些偏置信号,我们使用环境的3D GNSS仿真模型补偿了NLOS偏置。我们使用3D模型作为先验信息来表征其他NLOS偏差。在这项工作中,我们建议将基于3D模型的信号表征深入集成到称为矢量跟踪环的高级GNSS接收器体系结构中。提出的体系结构是矢量跟踪接收器和外部本地信息协处理器的组合,用于校正GNSS测量。实际GPS信号获得的结果说明了这种方法在提高城市峡谷中导航解决方案的准确性和可靠性方面的有效性。

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