As the dependence of Global Navigation Systems (GNSS) increases, so does a growing demand for GNSS accuracy in urban environments. This research aims to improve navigation in these environments by integrating non‐line‐of‐sight signals, building models, and measured signal to noise ratios in ways not typically used in GNSS positioning. We propose a technique of combining elements of shadow matching, non‐line‐of‐sight signal prediction through ray tracing, and collaborative navigation. A specularity metric is developed, which predicts the likelihood of building reflections resulting in non‐line‐of‐sight signal reception, and is used in conjunction with shadow matching techniques to improve positioning. A framework for implementing these approaches is presented and demonstrated using improved positioning techniques built and tested using real‐world data collected in urban surroundings.

中文翻译：

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通过阴影匹配和镜面反射匹配来改善城市导航

随着全球导航系统（GNSS）的依赖性增加，在城市环境中对GNSS精度的需求也在不断增长。这项研究旨在通过以GNSS定位中通常不使用的方式集成非视线信号，构建模型和测得的信噪比来改善这些环境中的导航。我们提出了一种将阴影匹配，通过射线跟踪的非视线信号预测以及协作导航相结合的技术。开发了一种镜面反射度度量，可以预测建筑物反射导致非视线信号接收的可能性，并将其与阴影匹配技术结合使用以改善定位。