Indoor Localization Using Magnetic Field Strength Pattern 


Vol. 44,  No. 8, pp. 1510-1519, Aug.  2019
10.7840/kics.2019.44.8.1510


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  Abstract

Conventional geomagnetic field strength-based indoor photometric technique determine the user"s position by comparing the database with the geomagnetic field strength collected by the user. However, the magnetic field strength of different geomagnetic fields is collected at the same point as the sensor of magnetic field is disadvantage is that the greater the difference between the geomagnetic field strength stored in the database and the geomagnetic field strength collected by the user, the lower the degree of location accuracy, and the problem of having to build a new database for each smartphone variant. In order to solve these problems, this paper proposes a geomagnetic field strength patterned MP (Magnetic Pattern) and a geo-magnetic field strength using CNN (Convolutional Neural Networks). The database construction phase of the proposed technique produces MPs that can occur at the points to be measured, and the station phase predicts the user"s position by learning the generated MPs from the composite neural network. To evaluate the performance of the proposed technique, Samsung Galaxy S8 and LG G6 were evaluated in two buildings with different experimental environments.

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  Cite this article

[IEEE Style]

M. Kang, Y. Im, S. Hur, Y. Park, "Indoor Localization Using Magnetic Field Strength Pattern," The Journal of Korean Institute of Communications and Information Sciences, vol. 44, no. 8, pp. 1510-1519, 2019. DOI: 10.7840/kics.2019.44.8.1510.

[ACM Style]

Min-gyu Kang, Yeong-jun Im, Soo-jung Hur, and Yong-wan Park. 2019. Indoor Localization Using Magnetic Field Strength Pattern. The Journal of Korean Institute of Communications and Information Sciences, 44, 8, (2019), 1510-1519. DOI: 10.7840/kics.2019.44.8.1510.

[KICS Style]

Min-gyu Kang, Yeong-jun Im, Soo-jung Hur, Yong-wan Park, "Indoor Localization Using Magnetic Field Strength Pattern," The Journal of Korean Institute of Communications and Information Sciences, vol. 44, no. 8, pp. 1510-1519, 8. 2019. (https://doi.org/10.7840/kics.2019.44.8.1510)

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pISSN : 1226 - 4717
eISSN : 2287 - 3880