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作者:

Tang, Peng (Tang, Peng.) | Huang, Zhiqing (Huang, Zhiqing.) | Lei, Jun (Lei, Jun.)

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EI Scopus

摘要:

In this paper, we proposed an indoor localization technique which use WLAN fingerprint and magnetic field fingerprint with landmarks detection. First, we use WLAN RSS fingerprint and magnetic field fingerprint to improve fingerprint's spatial and time characterization and localization accuracy. Second against the special position like stairs, elevators, etc., we mark the special position as landmarks and use the accelerometer sensor data to detect whether the user is in the special position. Through landmarks detection we can reduce the impact of the limitations of location fingerprinting positioning effectively and improve the localization algorithm's efficiency. Experimental results show that, compared to a single widely used WLAN RSS fingerprint localization algorithm, the proposed algorithm can effectively improve the accuracy and efficiency of indoor location. © 2017 IEEE.

关键词:

Efficiency Indoor positioning systems Intelligent computing Magnetic fields Palmprint recognition Wireless local area networks (WLAN)

作者机构:

  • [ 1 ] [Tang, Peng]Faculty of Information Technology, Beijing University of Technology, Beijing Engineering Research Center for IoT Software and Systems, Beijing, China
  • [ 2 ] [Huang, Zhiqing]Faculty of Information Technology, Beijing University of Technology, Beijing Engineering Research Center for IoT Software and Systems, Beijing, China
  • [ 3 ] [Lei, Jun]Faculty of Information Technology, Beijing University of Technology, Beijing Engineering Research Center for IoT Software and Systems, Beijing, China

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年份: 2017

语种: 英文

被引次数:

WoS核心集被引频次: 0

SCOPUS被引频次: 7

ESI高被引论文在榜: 0 展开所有

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