Magnetic Fingerprinting for Indoor Localisation in a Social Interaction Setting
S. Vacanas (TU Delft - Electrical Engineering, Mathematics and Computer Science)
H.S. Hung – Mentor (TU Delft - Electrical Engineering, Mathematics and Computer Science)
S. Tan – Mentor (TU Delft - Electrical Engineering, Mathematics and Computer Science)
M. Kok – Mentor (TU Delft - Mechanical Engineering)
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Abstract
Results show that combined dual-sensor features consistently outperform single-sensor variants, and that coarser grids yield higher exact accuracy while mean physical error remains stable across resolutions at approximately 70–80 cm. At 0.5 m resolution, the best configuration places 71% of predictions within 50 cm of the true location, approaching the accuracy of a UWB baseline system while requiring no installed infrastructure. Zone merging and hexagonal tessellation do not provide consistent improvements over the plain square grid, suggesting that magnetic ambiguity rather than data imbalance or cell geometry is the dominant source of error. The findings demonstrate that infrastructure-free magnetic fingerprinting is a practically viable approach for coarse spatial awareness in socially dynamic indoor environments.