Design and Implementation of MARG Sensors Based Positioning Method Using a Mobile Phone

Abstract

Due to the problems of high cost and complication in indoor positioning, a new kind of positioning method by using a mobile phone based on magnetic, angular, rate, and gravity (MARG) sensors is more favored in recent years. This method estimates the orientation of pedestrian by quaternion. The quaternion-based extended Kalman filter (EKF) used for data fusion and orientation correction reduces the error of linear acceleration and avoids magnetic-field interference. We conduct pedestrian gait detection and step length estimation by using an accelerometer and verify the positioning performance of this method in an mobile phone. Testing results indicate that the positioning accuracy can reach 30 ‰ and 20 ‰ in the complex magnetic-field and non-magnetic interference environments respectively.