A Hybrid Marker-Based Indoor Positioning System for Pedestrian Tracking in Subway Stations

Abstract

The use of smartphones for accurate navigation in underground spaces, such as subway stations, poses several challenges. This is because it is difficult to obtain a sure estimate of user location due to the radio signal interference caused by the entry and exit of trains, the infrastructure of the subway station installation, and changes in the internal facility environment. This study uses quick response markers and augmented reality to solve these difficulties using an error correction method. Specifically, a hybrid marker-based indoor positioning system (HMIPS) which provides accurate and efficient user-tracking results is proposed. The HMIPS performs hybrid localization by using marker images as well as inertial measurement unit data from smartphones. It utilizes the Viterbi tracking algorithm to solve the problem of tracking accuracy degradation that may occur when inertial sensors are used by adopting a sensor error correction technique. In addition, as an integrated system, the HMIPS provides a tool to easily carry out all the steps necessary for positioning. The results of experiments conducted in a subway station environment confirm that the HMIPS provides accurate and practical navigation services. The proposed system is expected to be useful for indoor navigation, even in poor indoor positioning environments.