Floor positioning method indoors with smartphone’s barometer
This paper presents an indoor floor positioning method with the smartphone’s barometer for the purpose of solving the problem of low availability and high environmental dependence of the traditional floor positioning technology. First, an initial floor position algorithm with the “entering” detectio...
Main Authors: | , , , |
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Format: | Article |
Language: | English |
Published: |
Taylor & Francis Group
2019-04-01
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Series: | Geo-spatial Information Science |
Subjects: | |
Online Access: | http://dx.doi.org/10.1080/10095020.2019.1631573 |
Summary: | This paper presents an indoor floor positioning method with the smartphone’s barometer for the purpose of solving the problem of low availability and high environmental dependence of the traditional floor positioning technology. First, an initial floor position algorithm with the “entering” detection algorithm has been obtained. Second, the user’s going upstairs or downstairs activities are identified by the characteristics of the air pressure fluctuation. Third, the moving distance in the vertical direction and the floor change during going upstairs or downstairs are estimated to obtain the accurate floor position. In order to solve the problem of the floor misjudgment from different mobile phone’s barometers, this paper calculates the pressure data from the different cell phones, and effectively reduce the errors of the air pressure estimating the elevation which is caused by the heterogeneity of the mobile phones. The experiment results show that the average correct rate of the floor identification is more than 85% for three types of the cell phones while reducing environmental dependence and improving availability. Further, this paper compares and analyzes the three common floor location methods – the WLAN Floor Location (WFL) method based on the fingerprint, the Neural Network Floor Location (NFL) methods, and the Magnetic Floor Location (MFL) method with our method. The experiment results achieve 94.2% correct rate of the floor identification with Huawei mate10 Pro mobile phone. |
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ISSN: | 1009-5020 1993-5153 |