Skip to main content
Log in

A Platform Control Algorithm for Long-endurance Hybrid Inertial Navigation System with Fiber Optic Gyroscope

  • PHYSICAL INSTRUMENTS FOR ECOLOGY, MEDICINE, AND BIOLOGY
  • Published:
Instruments and Experimental Techniques Aims and scope Submit manuscript

Abstract

Hybrid inertial navigation system is a new solution to increase long-endurance navigation performance based on fiber optic gyroscope. It relies on rotational mechanism tracking navigation coordinate system and isolating carrier’s angular motion with static error free, while realizing rotational modulation at the same time. The output of gyroscope is always used to calculate control command. However, the axis of gyroscope and the axis of motor are nonorthogonal because of rotation modulation and carrier’s motion. Therefore, it is necessary to study an effective platform control algorithm achieving both stabilization and rotation modulation. The paper proposes a platform control algorithm for tri-axis hybrid inertial navigation system. Experiments are conducted to verify the method using a self-researched hybrid navigation system. According to experimental results, the proposed method has an advantage over the traditional method.

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

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1.
Fig. 2.
Fig. 3.
Fig. 4.
Fig. 5.
Fig. 6.
Fig. 7.

Similar content being viewed by others

REFERENCES

  1. Feng, P.-D., J. Chin. Inertial Technol., 2016, vol. 24, no. 3 p. 281. https://doi.org/10.13695/j.cnki.12-1222/o3.2016.03.001

    Article  Google Scholar 

  2. Liu, B., Wei, S., Su, G., Wang, J., and Lu, J., Sensors, 2018, vol. 18, no. 5, p. 1303. https://doi.org/10.3390/s18051303

    Article  ADS  Google Scholar 

  3. Ben, Y., Wu, X., Chai, Y., and Li, Q., Proc. 2011 IEEE/ICME Int. Conference on Complex Medical Engineering, Harbin, 2011, p. 293. https://doi.org/10.1109/ICCME.2011.5876753

  4. Chang, G., Xu, J., Li, A., and Cheng, K., Proc. 2010 Int. Conference on Measuring Technology and Mechatronics Automation, Changsha, 2010, vol. 2, p. 124, https://doi.org/10.1109/ICMTMA.2010.509

  5. Li, A., Chang, G., Qin, F., and Li, H., Proc. 2nd Int. Asia Conference on Informatics in Control, Automation and Robotics (CAR 2010), Wuhan, 2010, vol. 1 p. 284. https://doi.org/10.1109/CAR.2010.5456846

  6. Xu, S.-H., Shi, J.-H., and Liang, G.-Q., J. Naval Aeronaut. Astronaut. Univ., 2014, vol. 29, no. 5, p. 405. https://doi.org/10.7682/j.issn.1673-1522.2014.05.002

    Article  Google Scholar 

  7. Zhang, L.-D., Lian, J.-X., and Hu, X.-P., J. Natl. Univ. Def. Technol., China, 2011, vol. 33, no. 4, p. 152.

  8. Chang, G.-B., Xu, J.-N., Li A., and Qin, F.-J, J. Chin. Inertial Technol., 2011, vol. 19, p. 175.

    Google Scholar 

  9. Liu, Z., Wang, L., Wang, W., and Gao, P., Microsyst. Technol., 2017, vol. 23, no. 12, p. 5423. https://doi.org/10.1007/s00542-016-3270-z

    Article  Google Scholar 

  10. Wang, L., Wang, W., Liu, Z.-J., and Song, T.-X., Acta Armamentarii, 2018, vol. 39, p. 1316. https://doi.org/10.3969/j.issn.1000-1093.2018.07.009

    Article  Google Scholar 

  11. Wang, L., Li, K., Chen, Y., Liu, J., and Xu, Y., Opt. Express, 2017, vol. 25, no. 25, p. 30956. https://doi.org/10.1364/OE.25.030956

    Article  ADS  Google Scholar 

  12. Morris, T.A., Wheeler, J.M., Grant, M.J., and Digonnet, M.J.F., Proc. 7th European Workshop on Optical Fiber Sensors (EWOFS19), Limassol, 2019, p. 111990T. https://doi.org/10.1117/12.2542713

  13. Zhang, C., Mao, Y., Tian, J., and Li, Z., Proc. AOPC 2015: Optical Fiber Sensors and Applications (AOPC2015), Beijing, 2015, vol. 9679, p. 96791B. https://doi.org/10.1117/12.2203287

  14. Ren, W., Luo, Y., He, Q., Zhou, X., Deng, C., Mao, Y., and Ren, G., IEEE Sens. J., 2018, vol. 18. no. 19, p. 8172. https://doi.org/10.1109/JSEN.2018.2835147

    Article  ADS  Google Scholar 

  15. Grifi, D., Senatore, R., Quatraro, E., Verola, M., and Pizzarulli, A., Proc. 2017 DGON Inertial Sensors and Systems (ISS), Karlsruhe, 2017, p. 1. https://doi.org/10.1109/InertialSensors.2017.8171492

    Book  Google Scholar 

  16. Sokolov, A.V., Krasnov, A.A., Starosel’tsev, L.P., and Dzyuba, A.N., Gyroscopy Navig., 2015, vol. 6, no. 4, p. 338. https://doi.org/10.1134/S2075108715040124

    Article  Google Scholar 

  17. Luo, Y., Ren, W., Huang, Y., He, Q., Wu, Q., Zhou, X., and Mao, Y., Electronics, 2018, vol. 7, no. 10, p. 223. https://doi.org/10.3390/electronics7100223

    Article  Google Scholar 

  18. Yongyuan, Q., Inertial Navigation, Beijing: Science Press, 2006.

    Google Scholar 

  19. Wang, L., Wang, W., Wang, X.-Y., and Yang, G.-L., J. Control Decis., 2014, vol. 464, no. 1, p. 195. https://doi.org/10.13195/j.kzyjc.2013.0850

    Article  Google Scholar 

Download references

ACKNOWLEDGMENTS

This work was supported by the Aeronautical Science Foundation of China (no. 20175851030).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Lei Wang.

Ethics declarations

The authors declare that they have no conflicts of interest.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Ban, J., Wang, L. & Chen, G. A Platform Control Algorithm for Long-endurance Hybrid Inertial Navigation System with Fiber Optic Gyroscope. Instrum Exp Tech 65, 645–652 (2022). https://doi.org/10.1134/S0020441222040194

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1134/S0020441222040194

Navigation