User Displacement Estimation in Indoor Environments with Smartphone using Runge-Kutta Method

Abstract

Estimating user position in indoor environments relative to the indoor space is a challenging problem. Especially when it must be obtained without infrastructure or any added costs to install the system. User displacement estimation in Indoor environments with smartphone using Runge-Kutta method presents efficient method using self-contained inertial sensors with no additional infrastructure to solve this problem. The accelerometer, the rotation sensor and the magnetometer sensor are three main sensors used in this method. The algorithm derives the user position with Runge-Kutta method using inertial data collected from the user smartphone while the user is in motion. The magnetometer data is used to self-correct the any existing noise in the user displacement. This method was experimented for various user motions like walking, wheelchair and driving. The results demonstrate that accumulated error rate and heading error rate were significantly reduced.