KSII Transactions on Internet and Information Systems (TIIS)

Korean Society for Internet Information (한국인터넷정보학회)
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BtPDR: Bluetooth and PDR-Based Indoor Fusion Localization Using Smartphones

  • Yao, Yingbiao (School of communication Engineering, Hangzhou Dianzi University) ;
  • Bao, Qiaojing (School of communication Engineering, Hangzhou Dianzi University) ;
  • Han, Qi (School of communication Engineering, Hangzhou Dianzi University) ;
  • Yao, Ruili (School of communication Engineering, Hangzhou Dianzi University) ;
  • Xu, Xiaorong (School of communication Engineering, Hangzhou Dianzi University) ;
  • Yan, Junrong (School of communication Engineering, Hangzhou Dianzi University)
  • Received : 2016.12.22
  • Accepted : 2018.04.06
  • Published : 2018.08.31
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Abstract

This paper presents a Bluetooth and pedestrian dead reckoning (PDR)-based indoor fusion localization approach (BtPDR) using smartphones. A Bluetooth and PDR-based indoor fusion localization approach can localize the initial position of a smartphone with the received signal strength (RSS) of Bluetooth. While a smartphone is moving, BtPDR can track its position by fusing the localization results of PDR and Bluetooth RSS. In addition, BtPDR can adaptively modify the parameters of PDR. The contributions of BtPDR include: a Bluetooth RSS-based Probabilistic Voting (BRPV) localization mechanism, a probabilistic voting-based Bluetooth RSS and PDR fusion method, and a heuristic search approach for reducing the complexity of BRPV. The experiment results in a real scene show that the average positioning error is < 2m, which is considered adequate for indoor location-based service applications. Moreover, compared to the traditional PDR method, BtPDR improves the location accuracy by 42.6%, on average. Compared to state-of-the-art Wireless Local Area Network (WLAN) fingerprint + PDR-based fusion indoor localization approaches, BtPDR has better positioning accuracy and does not need the same offline workload as a fingerprint algorithm.

Keywords

References

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