Real Time Adaptive Step Length Estimation for Smartphone User

Abstract

An indoor positioning with a high accuracy is still a challenging research area. The error of pedestrian dead reckoning (PDR) is usually caused from both heading and step length error. In this paper, we focus on the reducing of step length estimation. We apply a linear combination consisted of 4 parameters obtained from an acceleration, an angular velocity, and a pedestrian average step length. For an in-flight calibration of step length estimation, we utilize map information and calculate constants for linear combination. We conduct a field test and its result suggests that the proposed algorithm is more accurate than the fixed step length method.