Indoor localization using magnetic field anomalies and inertial measurement units based on Monte Carlo localization

Abstract

Localization in indoor environments has become increasingly important for various applications which require precise indoor tracking and navigation. In this paper, a system employing magnetic field anomalies and inertial navigation systems is proposed to address the problem of indoor localization. The proposed system consists of a network of magnetometers, inertial measurement units (accelerometer and gyroscope) and motion detection as well as nearest neighbors algorithms incorporated inside Monte Carlo localization (MCL). From the experiments performed, it is found that every location in a given indoor environment has its own almost unique magnetic field value. And by integrating this local variation of magnetic field with MCL algorithm, infrastructure independent indoor localization system is presented. Furthermore, the simulation results show effective indoor localization is possible using the proposed techniques.