Exploiting wearable devices for the calibration of inertial navigation systems

Wearable devices have many applications, pedestrian navigation among them. In this case, the inertial measurement unit (IMU) is embedded in the wearable device. Moreover, inertial navigation systems (INSs) based on non-foot-mounted IMUs use the step-length-and-heading estimation approach. The latter requires the calibration of the empirical model to estimate the step length. In this work, we propose a method to automatically calibrate empirical models for the step length estimation. Two IMUs are used. The first one is located in some part of the user's body, e.g. the thigh, and it serves the purpose of the inertial navigation. The second is embedded in the shoe, and it is used to calibrate the empirical model of the first IMU. We obtain two main results. Firstly, the calibration is only required during the first two minutes. Secondly, the automatic calibration reduces the distance error in both its mean and standard deviation. This work is subject of a patent application