Rotation-Invariant Magnetic Features for Inertial Indoor-Localization

Indoor-Localization using mobile end-user devices such as smartphones remains a highly discussed research topic. Applications range from guidance in large structures, assistance of visually impaired or even localization and guidance in rescue operations. Current approaches are often based on Radio-Frequency strength localization, which show insufficient precision and robustness. In this paper we investigate a magneto-based approach using rotation-invariant features compared with a pre-recorded grid-based map. Furthermore, we show, how this approach can be combined with relative localization using step recognition from inertial measurements. We test and evaluate both systems in simulation as well as real-world tests. We show, that a sub-meter precision localization accuracy can be reached using our magneto-intertial approach.