Terrain navigation in the magnetic landscape: Particle filtering for indoor positioning

Abstract

Variations in the ambient magnetic field can be used as features in indoor positioning and navigation. We describe a technique for map matching where the pedestrian movement is matched to a map of the magnetic landscape. The map matching algorithm is based on a particle filter, a recursive Monte Carlo method, and follows the classical terrain matching framework used in aircraft positioning and navigation. A recent probabilistic Gaussian process regression based method for modeling the ambient magnetic field is employed in the framework. The feasibility of this terrain matching approach is demonstrated in a simple real-life indoor positioning example, where both the mapping and positioning is done using a smartphone device.