MEMS IMU Based Pedestrian Indoor Navigation for Smart Glass

Abstract

In open air environment, Global Positioning System (GPS) receiver can determine its position with very high accuracy. Inside a building the GPS signal is degraded, the position estimation from the GPS receiver is very erroneous and of no practical use. In this paper, we present an indoor navigation system to track the position of a pedestrian by using built-in inertial measurement unit (IMU) sensors of a smart eyeglass. The device used for this project was an intelligent eye-wear "JINS MEME". Here algorithm for step detection, heading and stride estimation are used to estimate the position based on the known locations of the walker using Pedestrian Dead Reckoning method (PDR). We have used extended Kalman filters as sensor fusion algorithm, where measurements of acceleration and orientation from IMU are used to track user's movement, pace, and heading. The results showed that the level of accuracy was entirely acceptable. Average deviancy between the estimated and real position was less than 1.5 m for short range of walk was accomplished. There are some ideas for further development. Increasing the accuracy of the position estimation by palliation of stride length estimation error was identified as the most essential.