@inproceedings{706ad42a50d74bad8d82da815dbb79eb,
title = "The research of stance-phase detection to improve ZUPT-aided pedestrian navigation system",
abstract = "Inertial navigation is a fundamental method for pervasive indoor tacking and navigation. Although PDR based on inertial navigation can achieve robust indoors and outdoors positioning, the positioning accuracy does not meet the accuracy we need, due to the error divergence of the system. We present ZUPT with Kalman filter, a precise, robust technique tracks well even when presented with very noisy sensor data. Key to our ZUPT is zero velocity detection, the step to determine if the person's foot is in stance phase during walking. We used three different methods to detect zero velocity moments and compare their accuracy. Finally, we found that ZUPT using asymptotic zero velocity detection greatly improved the accuracy of inertial navigation. We believe that such a convergent and high precision approach will improve the application of inertial navigation in indoor positioning.",
keywords = "EKF, PDR, ZUPT",
author = "Yang, {Ming Kun} and Jianbo Liang and Zhuoling Xiao and Bo Yan and Liang Zhou and Shuisheng Lin and Xinchun Liu",
note = "Publisher Copyright: {\textcopyright} 2019 IEEE; 2019 IEEE International Symposium on Circuits and Systems, ISCAS 2019 ; Conference date: 26-05-2019 Through 29-05-2019",
year = "2019",
doi = "10.1109/ISCAS.2019.8702815",
language = "English",
series = "Proceedings - IEEE International Symposium on Circuits and Systems",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2019 IEEE International Symposium on Circuits and Systems, ISCAS 2019 - Proceedings",
address = "United States",
}