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.