A Hidden Markov Model for Indoor User Tracking Based on WiFi Fingerprinting and Step Detection

M.K. Hoang, J. Schmalenstroeer, C. Drueke, D.H. Tran Vu, R. Haeb-Umbach, in: 21th European Signal Processing Conference (EUSIPCO 2013), 2013.

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In this paper we present a modified hidden Markov model (HMM) for the fusion of received signal strength index (RSSI) information of WiFi access points and relative position information which is obtained from the inertial sensors of a smartphone for indoor positioning. Since the states of the HMM represent the potential user locations, their number determines the quantization error introduced by discretizing the allowable user positions through the use of the HMM. To reduce this quantization error we introduce â??pseudoâ?? states, whose emission probability, which models the RSSI measurements at this location, is synthesized from those of the neighboring states of which a Gaussian emission probability has been estimated during the training phase. The experimental results demonstrate the effectiveness of this approach. By introducing on average two pseudo states per original HMM state the positioning error could be significantly reduced without increasing the training effort.
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21th European Signal Processing Conference (EUSIPCO 2013)
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Hoang MK, Schmalenstroeer J, Drueke C, Tran Vu DH, Haeb-Umbach R. A Hidden Markov Model for Indoor User Tracking Based on WiFi Fingerprinting and Step Detection. In: 21th European Signal Processing Conference (EUSIPCO 2013). ; 2013.
Hoang, M. K., Schmalenstroeer, J., Drueke, C., Tran Vu, D. H., & Haeb-Umbach, R. (2013). A Hidden Markov Model for Indoor User Tracking Based on WiFi Fingerprinting and Step Detection. In 21th European Signal Processing Conference (EUSIPCO 2013).
@inproceedings{Hoang_Schmalenstroeer_Drueke_Tran Vu_Haeb-Umbach_2013, title={A Hidden Markov Model for Indoor User Tracking Based on WiFi Fingerprinting and Step Detection}, booktitle={21th European Signal Processing Conference (EUSIPCO 2013)}, author={Hoang, Manh Kha and Schmalenstroeer, Joerg and Drueke, Christian and Tran Vu, Dang Hai and Haeb-Umbach, Reinhold}, year={2013} }
Hoang, Manh Kha, Joerg Schmalenstroeer, Christian Drueke, Dang Hai Tran Vu, and Reinhold Haeb-Umbach. “A Hidden Markov Model for Indoor User Tracking Based on WiFi Fingerprinting and Step Detection.” In 21th European Signal Processing Conference (EUSIPCO 2013), 2013.
M. K. Hoang, J. Schmalenstroeer, C. Drueke, D. H. Tran Vu, and R. Haeb-Umbach, “A Hidden Markov Model for Indoor User Tracking Based on WiFi Fingerprinting and Step Detection,” in 21th European Signal Processing Conference (EUSIPCO 2013), 2013.
Hoang, Manh Kha, et al. “A Hidden Markov Model for Indoor User Tracking Based on WiFi Fingerprinting and Step Detection.” 21th European Signal Processing Conference (EUSIPCO 2013), 2013.

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