Pedestrian Stride-Length Estimation Algorithm Based on DTW Motion Mode Recognition

Abstract

In this paper, based on the characteristics of inertial data collected by smart terminals carried by pedestrians, a dynamic estimation algorithm of stride length using motion mode recognition is proposed. The motion mode includes pedestrian motion status and a smart terminal attitude. As pedestrians move forward, different motion modes will have a corresponding impact on the stride length estimation model, resulting in the stride length estimation model directly affecting the accuracy of the pedestrian dead reckoning system (PDR). Therefore, different motion modes need to make corresponding adjustments to the stride length estimation model to give a specific stride-length adjustment gain. In order to avoid errors caused by the change of the motion mode, a dynamic time warping (DTW) algorithm is proposed to identify the motion mode of the smart terminal, so as to select an appropriate gain to adjust the stride length estimation model, thereby improving the positioning accuracy of the pedestrian dead reckoning system. Experimental results show that the average positioning error of the stride-length estimation model based on DTW motion mode recognition is 1.78 meters in five motion modes. In performance, this algorithm is superior to other traditional stride length estimation models.