Cross-correlation data from GNSS signal tracking process collected using low-cost antenna

Global Navigation Satellite Systems (GNSS), such as GPS (Global Positioning System), are the most widely used technology for positioning and navigation. However, the accuracy and reliability of such positioning systems, and thus a variety of location-based services, decreases in urban canyon and (partially) denied GNSS environments. In such environments, GNSS signals can be blocked, reflected or attenuated. Those effects are particularly problematic for smartphone users, since smartphones make use of smaller, low-cost, and typically linearly polarised embedded GNSS antennae. As a result, smartphones struggle to receive and track line-of-sight GNSS signals, ultimately leading to positioning errors. This paper proposes and implements a solution based on correlation features to classify and detect line of sight signals on low-cost GNSS antenna. The paper demonstrates that correlation based features can be used for distinguishing between non-line of sight and line of sight GNSS signals, even in urban canyon or partially denied GNSS environments. This allows for the improved reliability of the final position solution, as well as providing a better understanding of the environment and its interaction with the navigation signals.全球导航卫星系统（Global Navigation Satellite Systems，GNSS），例如全球定位系统（Global Positioning System，GPS），是当前应用最为广泛的定位与导航技术。然而，在城市峡谷（urban canyon）以及GNSS信号部分受拒的环境中，这类定位系统乃至各类基于位置的服务（location-based services）的精度与可靠性均会下降。在此类环境下，GNSS信号可能被阻挡、反射或衰减。这类影响对智能手机用户而言尤为棘手，因为智能手机搭载的通常是尺寸小巧、成本低廉的嵌入式线性极化GNSS天线。因此，智能手机难以接收并跟踪视距（line-of-sight）GNSS信号，最终引发定位误差。本文提出并实现了一种基于相关特征的解决方案，用于在低成本GNSS天线上分类并检测视距信号。研究表明，即便在城市峡谷或GNSS信号部分受拒的环境中，基于相关特征的方法也可用于区分非视距（non-line-of-sight）与视距GNSS信号。这不仅能够提升最终定位解算结果的可靠性，还能帮助人们更深入地理解环境及其与导航信号的交互机制。