Pedestrian dead reckoning trajectory matching method for radio map crowdsourcing building in WiFi indoor positioning system

Abstract

Currently, WiFi positioning system based on fingerprint technology is becoming the first option for worldwide indoor positioning service. However, the biggest obstacle is the cost of radio map building when calibrating the reference point absolute position within the floor plan. An efficient method is to make use of pedestrian dead reckoning (PDR) by sampling the PDR trajectory as the reference point position. Unfortunately, it is valid only when the start point or/and the end point is known. Without knowing this information, the PDR trajectory sampling position is merely a relative position but not an absolute one, which could not be used to build the radio map, especially in the crowdsourcing way. In this paper, we propose an effective method to transform PDR trajectory position sampling from a relative one to an absolute one by matching PDR trajectory with the major possible trajectories within the floor plan. We introduce image processing method to match the PDR trajectory with all the major possible trajectories based on Hough transform, Harris corner detection. The simulation results show that the proposed method could succeed to provide the absolute position from the PDR trajectory, and offer a good radio map for localization in a crowdsourcing way.