Eung Sun Kim

Indoor positioning system using geomagnetic anomalies for smartphones

In this paper, we propose an indoor positioning system using smartphones. To localize the position of target that is pedestrian in usual indoors, we make use of perturbations of the geomagnetic field caused by structural steel elements in a building. The system based on magnetic field does not need any physical infrastructure, so it is possible to be realized with low cost. To estimate the targets position using the geomagnetic anomaly, the proposed system measures the magnetic field on its own position using a magnetometer embedded in smartphones and compares the sensor measurement with the magnetic map that has been created for the building in advance. The estimated position is calculated by a stochastic system based on the particle filter. To calculate control inputs for the particle filter, such as moving distance and direction, we exploit the inertial measurement unit (IMU) that is composed of 3-axis accelerometer and gyroscope built in the smartphone. The experimental results show that accuracy is within 3 meter. These results imply the potential to track people in the buildings that have geomagnetic map in advance at the meter scale using only smartphone with embedded sensors.

Ad hoc indoor peer-to-peer tracking using relative location estimation

We consider an ad hoc indoor device tracking problem where a user device has no knowledge of map and infrastructure. Since it does not have any information of reference points, the user device finds relative location of its target device. In fact, relative location, which can be described by direction and distance, is sufficient for the user device to track and approach the target device. However, indoor multipath environment and a single antenna of the device are obstacles to measuring direction using direction-of-arrival (DOA). Instead, if the user or the target device is moving, then, by fusing distance measurements and sensor information, the user device can estimate direction and thus calculate the relative location of the target. We show that the relative location can be calculated by trilateration in some cases. As a flexible and adaptable method, we also employ a simultaneous localization and mapping (SLAM)-based method using a particle filter (PF).We evaluate the ad hoc device tracking in some environments by simulation.