Abstract
The performance of inertial measurement unit (IMU) is very important for a pedestrian tracker. It is possible for an object to keep track of changes in its own position using an IMU. It is well known that the inertial element acts as the main hardware of IMU, but the accuracy of the inertial sensors degrades with time. The errors are mainly caused by the imperfect structure of the inertial element itself, the change of the internal physical factors and the change of the operating environment, etc. The performances of three IMUs which includes MPU9250, LSM9DS0 and BMX055 are analyzed in this paper. The parameters of the three sensors are compared. The typical error items for inertial elements and the principle and algorithm of the Allan Variance are introduced. Allan Variance technique is used to analyze errors of the inertial sensors. Finally, the design of IMU and the three IMU experimental results are introduced. Final results show that the performance of MPU9250 is the best and BMX055 is the worst.
This is a preview of subscription content, log in via an institution to check access.
References
Sukumar, C.F.P.T., Hazas, M.: Tutorial.: implementation of a pedestrian tracker using foot-mounted inertial sensors. IEEE Pervasive Comput. 12(2), 17–27 (2012)
Fourati, H.: Heterogeneous data fusion algorithm for pedestrian navigation via foot-mounted inertial measurement unit and complementary filter. IEEE Trans. Instrum. Measur. 64(1), 221–229 (2015)
Foxlin, E.: Pedestrian tracking with shoe-mounted inertial sensors. IEEE Comput. Graph. Appl. 25(6), 38–46 (2005)
El-Sheimy, N., Hou, H., Niu, X.: Analysis and modeling of inertial sensors using Allan variance. IEEE Trans. Instrum. Measur. 57(1), 140–149 (2008)
Allan, D.W.: Statistics of atomic frequency standards. Proc. IEEE 54(2), 221–230 (1966)
Xuefeng, Z., Xinyan, L.: Estimate method of MEMS gyroscope performance based on allan variance. Micronanoelectronic Technol. 8, 005 (2010)
Wen-hui, P., Wen-jie, C.: The recognition of MEMS gyroscope random error terms based on ALLAN variance. In: 2012 24th Chinese Control and Decision Conference (CCDC), pp. 1603–1606. IEEE (2012)
Skog, I., Handel, P., Nilsson, J.O., et al.: Zero-velocity detection—an algorithm evaluation. IEEE Trans. Biomed. Eng. 57(11), 2657–2666 (2010)
Madgwick, S.: An efficient orientation filter for inertial and inertial/magnetic sensor arrays. Report x-io and University of Bristol (UK), 25 (2010)
Hou H.: Modeling inertial sensors errors using Allan variance. Library and Archives Canada, Bibliothèque et Archives Canada (2005)
Acknowledgements
This work was partly supported by National Natural Science Foundation of China (61603284).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2017 Springer International Publishing AG
About this paper
Cite this paper
Zheng, J., Qi, M., Xiang, K., Pang, M. (2017). IMU Performance Analysis for a Pedestrian Tracker. In: Huang, Y., Wu, H., Liu, H., Yin, Z. (eds) Intelligent Robotics and Applications. ICIRA 2017. Lecture Notes in Computer Science(), vol 10462. Springer, Cham. https://doi.org/10.1007/978-3-319-65289-4_47
Download citation
DOI: https://doi.org/10.1007/978-3-319-65289-4_47
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-65288-7
Online ISBN: 978-3-319-65289-4
eBook Packages: Computer ScienceComputer Science (R0)