Demo: IMU−Aided Magneto−Inductive Localization
T. E. Abrudan‚ Zhuoling Xiao‚ A. Markham and N. Trigoni
In this work, we propose an infrastructure-based indoor localization system that exploits the predictable spatio-temporal features of a local magnetic field. The system also relies on inertial data in order to map the environment and track the user's location. Additionally, WiFi access points may be used to improve the performance.