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Author:

Liu, Yanhong (Liu, Yanhong.) | Ren, Mingrong (Ren, Mingrong.) | Wang, Pu (Wang, Pu.) | Guo, Hongyu (Guo, Hongyu.)

Indexed by:

EI Scopus

Abstract:

Pedestrian navigation system based on inertial sensors with low cost and small size, can realize independent positioning and do not need to install infrastructure in advance. Therefore, it receives extensive concerns both at home and abroad. While there has been little discussion about height error correction. When searching and rescuing in large buildings, vertical accuracy may seem to be more important than horizontal accuracy. In this paper, we study the detection of stance phase and present a floor matching algorithm to realize the height error correction. Firstly, we will distinguish floor phase from stair phase. A floor altitude database is built using prior knowledge and it can determine which floor the pedestrian is walking on for each given horizontal walking motion by matching altitude of each horizontal walking and the floor altitudes contained in the database. Finally, correct height error during the stance phase intervals when pedestrian is doing a horizontal walking motion. The experimental results show that the method can estimate which floor the pedestrian locates on and provide accurate height information, which can be applied in the actual rescue. © 2016 TCCT.

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Author Community:

  • [ 1 ] [Liu, Yanhong]School of Electronic Information and Control Engineering, Beijing University of Technology, Beijing; 100124, China
  • [ 2 ] [Liu, Yanhong]Engineering Research Center of Digital Community, Ministry of Education, Beijing; 100124, China
  • [ 3 ] [Ren, Mingrong]School of Electronic Information and Control Engineering, Beijing University of Technology, Beijing; 100124, China
  • [ 4 ] [Ren, Mingrong]Engineering Research Center of Digital Community, Ministry of Education, Beijing; 100124, China
  • [ 5 ] [Wang, Pu]Beijing Laboratory for Urban Mass Transit, Beijing; 100124, China
  • [ 6 ] [Guo, Hongyu]School of Electronic Information and Control Engineering, Beijing University of Technology, Beijing; 100124, China
  • [ 7 ] [Guo, Hongyu]Beijing Key Laboratory of Computational Intelligence and Intelligent Systems, China

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ISSN: 1934-1768

Year: 2016

Volume: 2016-August

Page: 5683-5686

Language: English

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count: 1

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 1

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