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Accuracy of Multimodal Pedestrian Localisation in Different Terminal Contexts

We present first results from extensive indoor localisation measurements. Our main objective is to understand the importance of different sensor modalities in high-accuracy localisation and tracking of modern terminal equipment such as smartphones. In our measurements, we have gathered Wi-Fi signal strength, accelerometer, magnetometer and compass readings over several trajectories in a typical office building, together with the ground truth locations of the user. We process all the combinations of these together with possibly known environmental constraints using state-of-the-art Bayesian filtering to estimate achievable localisation accuracy. Our initial results show that while relatively good median accuracy can be achieved by the use of, e.g., signal strength data alone, fusion of different data sources significantly reduces worst case errors and improves the topological correctness of the estimated user trajectories.