Open Access

ARTICLE

Localization Algorithm of Indoor Wi-Fi Access Points Based on Signal Strength Relative Relationship and Region Division

Wenyan Liu¹, Xiangyang Luo^1,*, Yimin Liu¹, Jianqiang Liu², Minghao Liu¹, Yun Q. Shi³

1 State Key Laboratory of Mathematical Engineering and Advanced Computing, Zhengzhou 450001, China .
2 School of Electronics and Communication Engineering, Zhengzhou University of Aeronautics, Zhengzhou 450001, China.
3 New Jersey Institute of Technology, NJ, USA.

* Corresponding author: Xiangyang Luo. Email: .

Computers, Materials & Continua 2018, 55(1), 71-93. https://doi.org/10.3970/cmc.2018.055.071

Abstract

Precise localization techniques for indoor Wi-Fi access points (APs) have important application in the security inspection. However, due to the interference of environment factors such as multipath propagation and NLOS (Non-Line-of-Sight), the existing methods for localization indoor Wi-Fi access points based on RSS ranging tend to have lower accuracy as the RSS (Received Signal Strength) is difficult to accurately measure. Therefore, the localization algorithm of indoor Wi-Fi access points based on the signal strength relative relationship and region division is proposed in this paper. The algorithm hierarchically divide the room where the target Wi-Fi AP is located, on the region division line, a modified signal collection device is used to measure RSS in two directions of each reference point. All RSS values are compared and the region where the RSS value has the relative largest signal strength is located as next candidate region. The location coordinate of the target Wi-Fi AP is obtained when the localization region of the target Wi-Fi AP is successively approximated until the candidate region is smaller than the accuracy threshold. There are 360 experiments carried out in this paper with 8 types of Wi-Fi APs including fixed APs and portable APs. The experimental results show that the average localization error of the proposed localization algorithm is 0.30 meters, and the minimum localization error is 0.16 meters, which is significantly higher than the localization accuracy of the existing typical indoor Wi-Fi access point localization methods.

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Keywords

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