<abstract xmlns="http://www.w3.org/1999/xhtml"><p>In this paper, a foot-mounted pedestrian navigation system using MEMS inertial sensors is implemented, where the zero-velocity detection is abstracted into a hidden Markov model with 4 states and 15 observations. Moreover, an observations extraction algorithm has been developed to extract observations from sensor outputs; sample sets are used to train and optimize the model parameters by the Baum-Welch algorithm. Finally, a navigation system is developed, and the performance of the pedestrian navigation system is evaluated using indoor and outdoor field tests, and the results show that position error is less than 3% of total distance travelled.</p></abstract>

In this paper, a foot-mounted pedestrian navigation system using MEMS inertial sensors is implemented, where the zero-velocity detection is abstracted into a hidden Markov model with 4 states and 15 observations. Moreover, an observations extraction algorithm has been developed to extract observations from sensor outputs; sample sets are used to train and optimize the model parameters by the Baum-Welch algorithm. Finally, a navigation system is developed, and the performance of the pedestrian navigation system is evaluated using indoor and outdoor field tests, and the results show that position error is less than 3% of total distance travelled.

Hidden Markov Model-based Pedestrian Navigation System using MEMS Inertial Sensors

Measurement Science Review

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

In this paper, a foot-mounted pedestrian navigation system using MEMS inertial sensors is implemented, where the zero-velocity detection is abstracted into a...

Hidden Markov Model-based Pedestrian Navigation System using MEMS Inertial Sensors

Pubblicato online: 11 mar 2015

Pagine: 35 - 43

Ricevuto: 04 lug 2014

Accettato: 25 feb 2015

DOI: https://doi.org/10.1515/msr-2015-0006

Parole chiave
Pedestrian navigation system, hidden Markov model, zero velocity detection, inertial sensors

© Yingjun Zhang, Wen Liu, Xuefeng Yang, Shengwei Xing

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Hidden Markov Model-based Pedestrian Navigation System using MEMS Inertial Sensors

Pubblicato online: 11 mar 2015

Pagine: 35 - 43

Ricevuto: 04 lug 2014

Accettato: 25 feb 2015

DOI: https://doi.org/10.1515/msr-2015-0006

Parole chiavePedestrian navigation system, hidden Markov model, zero velocity detection, inertial sensors

© Yingjun Zhang, Wen Liu, Xuefeng Yang, Shengwei Xing

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Parole chiave
Pedestrian navigation system, hidden Markov model, zero velocity detection, inertial sensors