Two-level Indoor Navigation using WiFi and MEMS Sensors
Authors
Yuliang Huang, Yongbo Zhang, Yi Cui, Zhihua Wang, Huimin Fu
Corresponding Author
Yuliang Huang
Available Online March 2018.
- DOI
- 10.2991/mmsa-18.2018.51How to use a DOI?
- Keywords
- indoor navigation, MEMS sensors, WiFi, extended kalman filter
- Abstract
In this paper, the indoor pedestrian location algorithm is investigated, in which we proposes a novel WiFi/MEMS integration structure for indoor navigation to fuse the information from WiFi and MEMS sensors. In WiFi part, aiming at the problem of large amount of calculation in the algorithm, a partition solution called “moving partition” is originally proposed. The test results from indoor experiments indicate that with “moving partition”, the computation time decreased by almost half and the proposed WiFi/MEMS solution works well, of which the mean positioning accuracy has been greatly improved compared with MEMS alone and WiFi alone.
- Copyright
- © 2018, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Yuliang Huang AU - Yongbo Zhang AU - Yi Cui AU - Zhihua Wang AU - Huimin Fu PY - 2018/03 DA - 2018/03 TI - Two-level Indoor Navigation using WiFi and MEMS Sensors BT - Proceedings of the 2018 International Conference on Mathematics, Modelling, Simulation and Algorithms (MMSA 2018) PB - Atlantis Press SP - 226 EP - 228 SN - 1951-6851 UR - https://doi.org/10.2991/mmsa-18.2018.51 DO - 10.2991/mmsa-18.2018.51 ID - Huang2018/03 ER -