OPTIMIZATION-BASED CALIBRATION OF MEMS NAVIGATION SYSTEM
Abstract
Technologies of autonomous wheeled robotic systems are becoming more and more in demand
lately. A separate type of application of such technology is an autonomous unmanned
ground vehicle. Unlike other types of transport (air, water), ground vehicles need to periodically
operate in full autonomy - when external communication with the infrastructure and other agents
of the transport network is inaccessible. In such circumstances, the issue of autonomous navigation
comes out on top, and increased requirements are imposed on positioning accuracy, especially
in an anthropogenic environment, for example, when driving in an urban environment, along
narrow mountain roads, and tunnels. One of the components of autonomous navigation is often an
inertial assembly consisting of several accelerometers, gyroscopes, and magnetometers. To obtain
a high-precision navigation solution based on an inertial assembly, it is required to properly calibrate
it. A separate issue is automation and its cost for further scaling necessary for mass production.
The article presents the theory and methodology for automated calibration of an inertial
navigation system based on MEMS sensors by solving an optimization problem. The proposed
technique does not require high-precision calibration equipment. The aim of the presented work is
to develop methods and theory for the calibration of inertial navigation units. The article formulates
general measurement models of sensors included in the inertial assembly, and proposes
methods for calibrating the parameters of accelerometers and gyroscopes fixed relative to each
other. The method of automation of the calibration process is presented, which does not require
high-precision equipment. The results of the application of the developed methods for the calibration
of a real inertial assembly are presented. A stand for automated calibration is presented.
References
2011, Vol. 12, No. 5, pp. 1157-1165.
2. Syed Z.F. [et al.]. A new multi-position calibration method for MEMS inertial navigation systems,
Measurement science and technology, 2007, Vol. 18. No. 7, pp. 1897.
3. Wang S., Meng N. A new Multi-position calibration method for gyroscope's drift coefficients
on centrifuge, Aerospace Science and Technology, 2017, Vol. 68, pp. 104-108.
4. Yang H. [et al.]. A novel tri-axial MEMS gyroscope calibration method over a full temperature
range, Sensors, 2018, Vol. 18, No. 9, pp. 3004.
5. Jia Y. [et al.]. Error analysis and compensation of MEMS rotation modulation inertial navigation
system, IEEE Sensors Journal, 2018, Vol. 18, No. 5, pp. 2023-2030.
6. Mones Z. [et al.]. A comparative study of gravitational acceleration cancellation from on-rotor
MEMS accelerometers for condition monitoring, 24th International Congress on Sound and
Vibration. International Institute of Acoustics and Vibration, IIAV, 2017.
7. Olivares A. [et al.]. High-efficiency low-cost accelerometer-aided gyroscope calibration, 2009
International Conference on Test and Measurement. IEEE, 2009, Vol. 1, pp. 354-360.
8. Choi K.Y., Jang S., Kim Y.H. Calibration of inertial measurement units using pendulum motion,
International Journal of Aeronautical and Space Sciences, 2010, Vol. 11, No. 3, pp. 234-239.
9. Wu Y., Pei L. Gyroscope calibration via magnetometer, IEEE Sensors Journal, 2017, Vol. 17,
No. 16, pp. 5269-5275.
10. Delgado J.V. [et al.]. Automatic calibration of low cost inertial gyroscopes with a PTU, 2016
IEEE 19th International Conference on Intelligent Transportation Systems (ITSC). IEEE,
2016, pp. 121-125.
11. Madgwick S.O.H. Automated calibration of an accelerometers, magnetometers and gyroscopes-
a feasibility study, Tehc Rep, x-io Technologies Limited, Bristol, UK. 2010.
12. Filatov Y.V. [et al.]. Dynamic calibration method of inertial measurement units, Microsyst.
Technol., 2015, Vol. 21, No. 11, pp. 2463-2467.
13. Hung J.C., Thacher J.R., White H.V. Calibration of accelerometer triad of an IMU with drifting
Z-accelerometer bias, Proceedings of the IEEE National Aerospace and Electronics Conference.
IEEE, 1989, pp. 153-158.
14. Grewal M.S., Henderson V.D., Miyasako R.S. Application of Kalman filtering to the calibration
and alignment of inertial navigation systems, 29th IEEE Conference on Decision and
Control. IEEE, 1990, pp. 3325-3334.
15. Kim M.S., Yu S.B., Lee K.S. Development of a high-precision calibration method for inertial
measurement unit, International journal of precision engineering and manufacturing, 2014,
Vol. 15, No. 3, pp. 567-575.
16. Cheuk C.M. [et al.]. Automatic calibration for inertial measurement unit, 2012 12th International
Conference on Control Automation Robotics & Vision (ICARCV). IEEE, 2012,
pp. 1341-1346.
17. Zhang R., Hoflinger F., Reind L.M. Calibration of an IMU using 3-D rotation platform, IEEE
sensors Journal, 2014, Vol. 14, No. 6, pp. 1778-1787.
18. Litvin M.A. [i dr.]. Tipy oshibok v inertsial'nykh navigatsionnykh sistemakh i metody ikh
approksimatsii [Types of errors in inertial navigation systems and methods of their approximation],
Informatsionnye protsessy [Information processes], 2014, Vol. 14, No. 4, pp. 326-339.
19. El-Diasty M., El-Rabbany A., Pagiatakis S. Temperature variation effects on stochastic
characteristics for low-cost MEMS-based inertial sensor error, Measurement Science and
Technology, 2007, Vol. 18, No. 11, pp. 3321.
20. Niu X. [et al.]. Fast thermal calibration of low-grade inertial sensors and inertial measurement
units, Sensors, 2013, Vol. 13, No. 9, pp. 12192-12217.
