@inproceedings{f66cc6677a794e10b5b6aa7dd8ee4e50,
title = "Wearable indoor pedestrian navigation based on MIMU and hypothesis testing",
abstract = "Indoor pedestrian navigation (IPN) has attracted more and more attention for the reason that it can be widely used in indoor environments without GPS, such as fire and rescue in building, underground parking, etc. Pedestrian dead reckoning (PDR) based on inertial measurement unit can meet the requirement. This paper designs and implements a miniature wearable indoor pedestrian navigation system to estimate the position and attitude of a person while walking indoor. In order to reduce the accumulated error due to long-term drift of inertial devices, a zero-velocity detector based on hypothesis testing is introduced for instantaneous velocity and angular velocity correction. A Kalman filter combining INS information, magnetic information, and zero transient correction information is designed to estimate system errors and correct them. Finally, performance testing and evaluation are conducted to the IPN; results show that for leveled ground, position accuracy is about 2% of the traveled distance.",
keywords = "EKF, Hypothesis testing, MIMU, Wearable indoor pedestrian navigation, ZUPT",
author = "Ma, {Xiao Fei} and Zhong Su and Xu Zhao and Liu, {Fu Chao} and Chao Li",
note = "Publisher Copyright: {\textcopyright} Zhejiang University Press and Springer Science+Business Media Singapore 2017.; International Conference on Wearable Sensors and Robots, ICWSR 2015 ; Conference date: 16-10-2015 Through 18-10-2015",
year = "2017",
doi = "10.1007/978-981-10-2404-7_10",
language = "English",
isbn = "9789811024030",
series = "Lecture Notes in Electrical Engineering",
publisher = "Springer Verlag",
pages = "111--122",
editor = "G.S. Virk and Canjun Yang and Huayong Yang",
booktitle = "Wearable Sensors and Robots - Proceedings of International Conference on Wearable Sensors and Robots 2015",
address = "Germany",
}