Skip to main content

High-Precision Calibration and Error Estimation of RLG SINS

  • Conference paper
  • First Online:
Multimedia Technology and Enhanced Learning (ICMTEL 2021)

Abstract

Since sensor errors limit navigation accuracy in ring laser gyroscope strapdown inertial navigation system (RLG SINS), the calibration of the error parameters is usually a key technology of SINS. This paper mainly studies the error estimation and high-precision calibration of RLG SINS under both static and small-angle swing bases using systematic calibration method. In this paper, firstly, based on the analysis of the error source, the error models of the quartz flexible accelerometers and laser gyroscopes are established. Meanwhile, according to the basic principles of SINS, the error equations of SINS in navigation coordinate system are derived. Then, this paper studies systematic calibration method. In this part, a multi position rotation error excitation method is introduced and a 33-dimensional Kalman filter is designed for the estimation of the error parameters. Finally, the simulation experiments for the error calibration of the inertial sensors under both static and small-angle swing conditions are performed to verify the effectiveness of this systematic calibration method. This method performs well in the simulation experiments and has its value in the online calibration of slight swing conditions, such as ship mooring state and the missile launcher swing state.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Tazartes, D.: An historical perspective on inertial navigation systems. In: 2014 International Symposium on Inertial Sensors and Systems, ISISS. IEEE, Laguna Beach (2014)

    Google Scholar 

  2. Nieminen, T., Kangas, J., Suuriniemi, S., et al.: An enhanced multi-position calibration method for consumer-grade inertial measurement units applied and tested. Meas. Sci. Technol. 21(10), 105204 (2010)

    Google Scholar 

  3. Gao, P., Li, K., Wang, L., et al.: A self-calibration method for accelerometer nonlinearity errors in triaxis rotational inertial navigation system. IEEE Trans. Instrum. Meas. 66(2), 243–253 (2017)

    Google Scholar 

  4. Cai, Q., Yang, G., Song, N., et al.: Online calibration of the geographic-frame-equivalent gyro bias in dual-axis RINS. IEEE Trans. Instrum. Meas. 67(7), 1609–1616 (2018)

    Article  Google Scholar 

  5. Li, K., Chen, Y., Wang, L.: Online self-calibration research of single-axis rotational inertial navigation system. Measurement 129, 633–641 (2018)

    Article  Google Scholar 

  6. Gao, P., Li, K., Song, T., et al.: An accelerometers-size-effect self-calibration method for triaxis rotational inertial navigation system. IEEE Trans. Industr. Electron. 65(2), 1655–1664 (2018)

    Article  Google Scholar 

  7. Glueck, M., Oshinubi, D., Manoli, Y.: Automatic real-time offset calibration of gyroscopes. Microsyst. Technol. 21(2), 429–443 (2014). https://doi.org/10.1007/s00542-014-2115-x

    Article  Google Scholar 

  8. Shi, W., Wang, X., Zheng, J., et al.: Multi-position systematic calibration method for RLG-SINS. Infrared Laser Eng. 45(11), 92–99 (2016)

    Google Scholar 

  9. Dranitsyna, E.V.: IMU calibration using sins navigation solution: selection of the rate table motion scenario. In: 2017 24th Saint Petersburg International Conference on Integrated Navigation Systems, ICINS, pp. 1–5. IEEE, St. Petersburg (2017)

    Google Scholar 

  10. Wang, Q., Wang, L., Qin, W., et al.: Continuous self-calibration path optimization design of inertial platform based on local observability analysis. J. Chin. Inertial Technol. 26(6), 713–720 (2018)

    Google Scholar 

  11. Cheng, J., Fang, J., Wu, W., et al.: Integrated calibration method for RLG IMU. J. Chin. Inertial Technol. 4, 445–452 (2014)

    Google Scholar 

  12. Jiang, P., Liang, H., Li, H.: Online calibration method of gyro constant drift for low-cost integrated navigator. In: 2019 5th International Conference on Control, Automation and Robotics, ICCAR 2019, pp. 846–850. IEEE (2019)

    Google Scholar 

  13. Ma, L., Chen, W., Li, B., et al.: Fast field calibration of MIMU based on the Powell algorithm. Sensors 14(9), 16062–16081 (2014)

    Article  Google Scholar 

  14. Qin, C., Chen, J., Han, Y., et al.: Online calibration method based on dual-axis rotation-modulating laser gyro SINS. In: Proceedings of the 28th Chinese Control and Decision Conference 2016, CCDC, pp. 3311–3315. IEEE, Yinchuan (2016)

    Google Scholar 

  15. Jiachong, C., Fei, Y., Ya, Z., et al.: A swing online calibration method of ship-based FOG-IMU. In: 2017 Forum on Cooperative Positioning and Service, CPGPS 2017, pp. 33–38. IEEE (2017)

    Google Scholar 

  16. Wang, Z., Shi, Z., Quan, Z.: Online calibration program of SINS for rocket. Infrared Laser Eng. 1, 266–272 (2015)

    Google Scholar 

  17. Wang, H., Shi, Z., Li, G., et al.: Research on simple online calibration scheme of missile SINS. J. Gun Launch Control 39(4), 6–15 (2018)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Xiyuan Chen .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2021 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Geng, Y., Chen, X. (2021). High-Precision Calibration and Error Estimation of RLG SINS. In: Fu, W., Xu, Y., Wang, SH., Zhang, Y. (eds) Multimedia Technology and Enhanced Learning. ICMTEL 2021. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 387. Springer, Cham. https://doi.org/10.1007/978-3-030-82562-1_44

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-82562-1_44

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-82561-4

  • Online ISBN: 978-3-030-82562-1

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics