## Motivation
Global navigation satellite system (GNSS) positioning accuracy is degraded in urban canyons due to signal blockages and reflections. This competition aims to foster the machine learning algorithms in GNSS multipath/NLOS problem. Totally there are three tasks for this problem, which is LOS/NLOS classification, Pseudorange Error Prediction, Positioning Prediction.

One of the important characteristics of the satellite is their visibility: whether they are light-of-sight (LOS) or non-light-of-sight (NLOS). This is the page for GNSS LOS/NLOS classifier performance evaluation platform. You can upload your prediction result to evaluate the performance of your model in a different scenario.

## Acknowledgements

We thanks the fellows who contribute to the project:
Prof. Hsu, Mr. Huang, Mr. Zhang, Mr. Ivan, Mr. Zhong, Mr. Max, Mr. Xu