This paper provides a hybrid approach between Wi-Fi and pedestrian dead reckoning (PDR) for the iPhones in indoor environments, and addresses the following two problems. First, since Apple Inc. no longer provides public information about currently-connected Wi-Fi (e.g., service set identifier, received signal strength and channel), Wi-Fi based pedestrian tracking apps that run on the iPhones are more restricted compared to other ones on the Android platforms. Second, even the PDR approach provides such a great way for self-localization, it suffers from accumulated errors of inertial sensors embedded in the smartphones. We propose a conversion function from a Wi-Fi status value to a proximity for the localization purpose. Then, a mobile iPhone collects mobility information from inertial measurements unit (IMU), inputs to the PDR, and combines with Wi-Fi proximity in order to perform accurate self-localization and tracking. Moreover, we improve the PDR by reducing drifting effects caused by the IMU biases. Experiment results show that the proposed scheme is effective and has low complexity, while bringing the benefits from smartphone IMU.
Pedestrian Indoor Localization and Tracking Using Hybrid Wi-Fi/PDR for iPhones
2021-04-01
2759027 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
IT-Lösung Lotsen nutzen Lagebildberichte auf iPhones und iPads
Online Contents | 2011
TAP1.11 Pedestrian Localization and Tracking System with Kalman Filtering
British Library Conference Proceedings | 2004
|