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Author:

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

Indexed by:

CPCI-S

Abstract:

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.

Keyword:

wlan fingerprint localization knn magnetic field ada-boost

Author Community:

  • [ 1 ] [Tang, Peng]Beijing Univ Technol, Beijing Engn Res Ctr IoT Software & Syst, Fac Informat Technol, Beijing, Peoples R China
  • [ 2 ] [Huang, ZhiQing]Beijing Univ Technol, Beijing Engn Res Ctr IoT Software & Syst, Fac Informat Technol, Beijing, Peoples R China
  • [ 3 ] [Lei, Jun]Beijing Univ Technol, Beijing Engn Res Ctr IoT Software & Syst, Fac Informat Technol, Beijing, Peoples R China

Reprint Author's Address:

  • [Tang, Peng]Beijing Univ Technol, Beijing Engn Res Ctr IoT Software & Syst, Fac Informat Technol, Beijing, Peoples R China

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Source :

2017 3RD IEEE INTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE & COMMUNICATION TECHNOLOGY (CICT)

Year: 2017

Language: English

Cited Count:

WoS CC Cited Count: 2

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 0

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