GA-PDR: Using Gait Analysis for Heading Estimation in PDR Based Indoor Localization System

Indoor positioning in the firefighting ground shows promising application prospects for enhancing rescue safety and efficiency. Low visibility and signal interference caused by smoke pose significant difficulties for visual Simultaneous Localization and Mapping (SLAM) systems and radio frequency-based localization methods, while the performance of existing pedestrian dead reckoning (PDR) methods is affected by unpredictable user gaits. This paper introduces a gait analysis-based PDR (GA-PDR) for deriving heading estimation in PDR to improve its localization performance. The proposed method determines the step pattern by analyzing the features of inertial measurement unit data, thereby enabling the classification of forward, left- and right-turn and around-turn from left or right-side movements. In addition, this study introduces a redundant turn elimination method to differentiate false positive patterns via a time-domain heading analysis for turn movements. The location tracking performance with the proposed GA-PDR approach is validated using a self-created dataset established under a smoke-filled experiment, the results of which indicate a lower loop closure error compared with the traditional PDR in all of the tested scenarios.