Pedestrian Navigation in Urban Area Using GNSS Raw Data with Smartphones

S. Miyai, Y. Amano and Y. Kubo

Abstract: In recent years, the pedestrian navigation technology using smartphones is utilized in various situations. This technology mainly depends on satellite navigation systems such as GPS (Global Positioning System), and it requires wave signals from four or more satellites. Therefore, in urban areas, we can not obtain accurate position information continuously due to a lot of obstacles such as tall buildings. In this paper, we propose a method to improve the positioning accuracy in urban areas by integrating raw data from satellites with sensors installed in smartphones through the Kalman filter and the Gaussian sum filter. Experimental results by these filters are compared, and it is shown that the Gaussian sum filter can take into account uncertainties of dynamics of the pedestrian, initial state and its statistics.
Published in: Proceedings of the 2020 International Technical Meeting of The Institute of Navigation
January 21 - 24, 2020
Hyatt Regency Mission Bay
San Diego, California
Pages: 660 - 671
Cite this article: Miyai, S., Amano, Y., Kubo, Y., "Pedestrian Navigation in Urban Area Using GNSS Raw Data with Smartphones," Proceedings of the 2020 International Technical Meeting of The Institute of Navigation, San Diego, California, January 2020, pp. 660-671.
https://doi.org/10.33012/2020.17169
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