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Mobile Information Systems
Volume 2016, Article ID 2369103, 15 pages
Research Article

Method for Improving Indoor Positioning Accuracy Using Extended Kalman Filter

1Cyber-Physical System Security Research Section, Electronics and Telecommunications Research Institute, 218 Gajeong-ro, Yuseoung-gu, Daejeon 34129, Republic of Korea
2Department of Computer Engineering, College of Engineering, Hannam University, 70 Hannam-ro, Daedeok-gu, Daejeon 34430, Republic of Korea

Received 4 March 2016; Revised 24 May 2016; Accepted 14 June 2016

Academic Editor: Sergio F. Ochoa

Copyright © 2016 Seoung-Hyeon Lee et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Beacons using bluetooth low-energy (BLE) technology have emerged as a new paradigm of indoor positioning service (IPS) because of their advantages such as low power consumption, miniaturization, wide signal range, and low cost. However, the beacon performance is poor in terms of the indoor positioning accuracy because of noise, motion, and fading, all of which are characteristics of a bluetooth signal and depend on the installation location. Therefore, it is necessary to improve the accuracy of beacon-based indoor positioning technology by fusing it with existing indoor positioning technology, which uses Wi-Fi, ZigBee, and so forth. This study proposes a beacon-based indoor positioning method using an extended Kalman filter that recursively processes input data including noise. After defining the movement of a smartphone on a flat two-dimensional surface, it was assumed that the beacon signal is nonlinear. Then, the standard deviation and properties of the beacon signal were analyzed. According to the analysis results, an extended Kalman filter was designed and the accuracy of the smartphone’s indoor position was analyzed through simulations and tests. The proposed technique achieved good indoor positioning accuracy, with errors of 0.26 m and 0.28 m from the average - and -coordinates, respectively, based solely on the beacon signal.