Volume 9 Number 4 (Oct. 2020)
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IJCCE 2020 Vol.9(4): 167-184 ISSN: 2010-3743
DOI: 10.17706/IJCCE.2020.9.4.167-184

Self-Adaptive Dynamic Ranging Model-Based Real-Time Hybrid Algorithm for Accurate Indoor Localization

Zhonghui Jiang, Wu Huang, Xiao Wei, Defu Cheng, Dan Li
Abstract—The reliability of location information still maintains a crucial impact on restricting the development of location based services in indoor environment. However, in wireless local area network, received signal strength indicator (RSSI) is prone to be interfered by indoor complex environment, resulting in low accuracy and instability of real-time positioning. Here, the new self-adaptive dynamic ranging model-based real-time hybrid algorithm was proposed to realize accurate and undisturbed localization in indoor scenes. A self-adaptive dynamic ranging model was initially constructed to update the environmental parameters and correct the ranging values of mobile terminals in real time. Based on this model, a hybrid KNN algorithm and a hybrid Bayesian algorithm were severally presented. Location fingerprint database and real-time RSSI data of test points were then obtained through data acquisition. Finally, the acquired data was further used to verify the two hybrid algorithms proposed, and compared with the results of several conventional algorithms. As a result, the stability and accuracy of dual hybrid algorithms were better than those of the traditional ones. The range of average location error of both hybrid algorithms maintained 1.26-1.38 m, which was significantly lower than the error level of 2-5 m under the current WLAN environment. This newly proposed hybrid algorithm could effectively improve the stability and accuracy of indoor localization with real-time positioning algorithm, providing a promising solution for RSSI-based indoor positioning system.

Index Terms—Hybrid intelligent systems, indoor environments, received signal strength indicator, simultaneous localization and mapping, wireless LAN.

Zhonghui Jiang, Xiao Wei, Defu Cheng, Dan Li are with Chengdu Techman Software Co., Ltd, Chengdu, China. Wu Huang is with Sichuan University, Chengdu, China.

Cite:Zhonghui Jiang, Wu Huang, Xiao Wei, Defu Cheng, Dan Li, "Self-Adaptive Dynamic Ranging Model-Based Real-Time Hybrid Algorithm for Accurate Indoor Localization," International Journal of Computer and Communication Engineering vol. 9, no. 4, pp. 167-184, 2020.

Copyright © 2020 by the authors. 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 (CC BY 4.0).

General Information

ISSN: 2010-3743 (Online)
Abbreviated Title: Int. J. Comput. Commun. Eng.
Frequency: Quarterly
Editor-in-Chief: Dr. Maode Ma
Abstracting/ Indexing: EI (INSPEC, IET), Google Scholar, Crossref, EBSCO, ProQuest, and Electronic Journals Library
E-mail: ijcce@iap.org
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