A Sensor-based Indoor Positioning Algorithm for Smart-Tour Applications
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Abstract
This article presents an indoor positioning algorithm using accelerometer, gyroscope, and magnetic sensors to determine the location of travel users, to provide location-based services for users on intelligent travel guide systems. The main contributions of the proposal method on this paper are the application of a Kalman filter to eliminate interference of sensor signals that are received from integrated sensors on common smartphones, to handle the time velocity drift when user moving smartphone while standing in place, and therefore, to increase the positioning accuracy. The experiment results show that the proposed positioning algorithm achieves decimeter accuracy in indoor environment, which is suitable for positioning applications such as smart-tour applications.
Keywords
Indoor Positioning Algorithm, Location-based Services, Kalman Filter
Article Details
References
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[2] Kalman RE and Bucy RS, “New results in linear filtering and prediction theory,” ASME. J. Basic Eng., vol. 83(1), pp. 95-108, 1961.
[3] Welch, Greg & Bishop, Gary, "An introduction to the Kalman filter," Proc. Siggraph Course, vol. 8, 2016.
[4] Quaternions and Rotations (Com S 477/577 Notes) Yan-Bin Jia Sep 5, 2017.
[5] Ruoyu Zhi, “A drift eliminated attitude & position estimation algorithm in 3D” (2016), Graduate College Dissertations and Theses, paper 450.