Wang, X and Wei, X and Liu, Y and Yang, K and Du, X (2017) Fingerprint-based Wi-Fi indoor localization using map and inertial sensors. International Journal of Distributed Sensor Networks, 13 (12). p. 155014771774981. DOI https://doi.org/10.1177/1550147717749817
Wang, X and Wei, X and Liu, Y and Yang, K and Du, X (2017) Fingerprint-based Wi-Fi indoor localization using map and inertial sensors. International Journal of Distributed Sensor Networks, 13 (12). p. 155014771774981. DOI https://doi.org/10.1177/1550147717749817
Wang, X and Wei, X and Liu, Y and Yang, K and Du, X (2017) Fingerprint-based Wi-Fi indoor localization using map and inertial sensors. International Journal of Distributed Sensor Networks, 13 (12). p. 155014771774981. DOI https://doi.org/10.1177/1550147717749817
Abstract
It is a common understanding that the localization accuracy can be improved by indoor maps and inertial sensors. However, there is a lack of concrete and generic solutions that combine these two features together and practically demonstrate its validity. This article aims to provide such a solution based on the mainstream fingerprint-based indoor localization approach. First, we introduce the theorem called reference points placement, which gives a theoretical guide to place reference points. Second, we design a Wi-Fi signal propagation-based cluster algorithm to reduce the amount of computation. The paper gives a parameter called reliability to overcome the skewing of inertial sensors. Then we also present Kalman filter and Markov chain to predict the system status. The system is able to provide high-accuracy real-time tracking by integrating indoor map and inertial sensors with Wi-Fi signal strength. Finally, the proposed work is evaluated and compared with the previous Wi-Fi indoor localization systems. In addition, the effect of inertial sensors’ reliability is also discussed. Results are drawn from a campus office building which is about 80 m×140 m with 57 access points.
Item Type: | Article |
---|---|
Uncontrolled Keywords: | Indoor localization; inertial sensors; map information |
Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science |
Divisions: | Faculty of Science and Health Faculty of Science and Health > Computer Science and Electronic Engineering, School of |
SWORD Depositor: | Unnamed user with email elements@essex.ac.uk |
Depositing User: | Unnamed user with email elements@essex.ac.uk |
Date Deposited: | 05 Jan 2018 13:40 |
Last Modified: | 16 May 2024 19:12 |
URI: | http://repository.essex.ac.uk/id/eprint/21012 |
Available files
Filename: 1550147717749817.pdf
Licence: Creative Commons: Attribution 3.0