Environmental context detection is a topic of interest for the navigation community since it enables to build a context-adaptive solution by choosing the proper data processing algorithm or by modifying the solution design itself.
We propose to build a supervised machine learning model which can robustly classify multiple contexts such as urban canyons, urban, trees and open-sky areas using GNSS data only.
A training and test database have been built with four datasets acquired at different times in order to prove the relevance of the solution.
These datasets are made available to the public for research purpose and can be downloaded by clicking here :
The choices of features and classifier are also discussed and compared to others papers. The classifier achieved an average 82.40% of classification accuracy.
Please cite our research work if using this dataset.