A fast path matching algorithm for indoor positioning systems using magnetic field measurements

The use of magnetic field (MF) measurements, unlike typical Wi-Fi or Bluetooth positioning measurements, are unaffected by moving humans, providing more time-invariant location information. We present a novel Fast Path Matching algorithm for MF and Inertial sensor measurements, FPM-MI, to localise a person using MF measurements fused with inertial sensor measurements. Our novelty is twofold: it has a reduced computational cost compared to a particle filter algorithm; it has a fast convergence performance, i.e., a person can walk a much shorter distance, about 3 m, to have an arm-span location accuracy. We validated our system in a library, a retail-like building, with multiple metal shelves and pillars, and determined the positioning error to be 1.8 m (90% confidence).

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