@inproceedings{947262e86abb4ee68ff5d899e9cbe946,
title = "A full dimension observable EKF in zero velocity state applied in SINS",
abstract = "Aiming at the problem that the traditional ZVU algorithm has low navigation accuracy and poor stability due to less observation and unreasonable parameter setting, a zero velocity state full dimension updating algorithm(ZVSU) is proposed in this paper. Different from the traditional ZVU algorithm, the ZVSU algorithm uses the system state of the adjacent time to calculate the measurements which cannot be observed directly at zero velocity state. Then the system will be full dimension observable. All the state errors can be estimated by EKF. In order to verify the accuracy and stability of the ZVSU algorithm, 10 sets of indoor personnel positioning experiments based on shoe-mounted IMU are carried out, and the ZVSU algorithm is compared with OpenShoe open source algorithm. The experimental results show that the positioning accuracy of the ZVSU algorithm is about 0.6\% of total travel distance. Under the same set of parameters, the positioning accuracy and stability of the ZVSU algorithm are better than that of OpenShoe open source algorithm.",
keywords = "Error Estimation, Extended Kalman Filter, Full Dimension Observation, Inertial Navigation, Strap-Down",
author = "Hui Zhao and Zong Su and Chao Li and Qing Li",
note = "Publisher Copyright: {\textcopyright} 2018 Technical Committee on Control Theory, Chinese Association of Automation.; 37th Chinese Control Conference, CCC 2018 ; Conference date: 25-07-2018 Through 27-07-2018",
year = "2018",
month = oct,
day = "5",
doi = "10.23919/ChiCC.2018.8482585",
language = "English",
series = "Chinese Control Conference, CCC",
publisher = "IEEE Computer Society",
pages = "4827--4832",
editor = "Xin Chen and Qianchuan Zhao",
booktitle = "Proceedings of the 37th Chinese Control Conference, CCC 2018",
address = "United States",
}