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Algorithms for Complexing an Inertial Navigation System with Angular Acceleration Sensors

https://doi.org/10.17587/mau.24.107-112

Abstract

In this paper the problem of increasing the accuracy of inertial navigation system of an aircraft in the absence of high-precision additional information sensors, such as GPS, has been studied. It is proposed to install angular acceleration sensors on the gyrostabilized platform of the inertial navigation system. The use of signals from the angular acceleration sensors made it possible to generate correction signals for the inertial navigation system. Correction algorithms have been developed in the structure of the inertial navigation system and in its output signal. The effectiveness of the developed algorithms has been demonstrated using semi-natural simulation with the Ts060K inertial navigation system.

About the Authors

K. A. Neusypin
Department of Informatics and Control Systems Bauman Moscow State Technical University
Russian Federation

Moscow



A. V. Proletarsky
Department of Informatics and Control Systems Bauman Moscow State Technical University
Russian Federation

Moscow



M. S. Selezneva
Department of Informatics and Control Systems Bauman Moscow State Technical University
Russian Federation

Associated Professor of the Department "Informatics and Control Systems", Bauman Moscow State Technical University, Cand. of Tech. Sc.

Moscow



References

1. Shen K. et al. Research on high-precision measurement systems of modern aircraft, Russian Aeronautics, 2018, vol. 61, no. 2, pp. 279—286.

2. Barbieri L. et al. Intercomparison of small unmanned aircraft system (sUAS) measurements for atmospheric science during the LAPSE-RATE campaign, Sensors, 2019, vol. 19, no. 9, pp. 2179.

3. Zhang L. et al. A new adaptive Kalman filter for navigation systems of carrier-based aircraft, Chinese Journal of Aeronautics, 2022, vol. 35, no. 1. pp. 416—425.

4. Javis R. A., Byrne J. C. Robot Navigation: Touching, seeing, and knowing, Proc. 1st Australian conference on artificial intelligence, 1986, vol. 69, pp. 18—20.

5. Chen D. et al. New algorithms for autonomous inertial navigation systems correction with precession angle sensors in aircrafts, Sensors, 2019, vol. 19, no. 22, p. 5016.

6. Jazwinski A. H. Stochastic processes and filtering theory, New York, Dover Publications, 2007.

7. Madyastha V. et al. Extended Kalman filter vs. error state Kalman filter for aircraft attitude estimation, AIAA Guidance, Navigation, and Control Conference, 2011, p. 6615.

8. Shakhtarin B. I., Shen Kai, Neusypin K. A. Modification of the nonlinear Kalman filter in a correction scheme of aircraft navigation systems, Journal of Communications Technology and Electronics, 2016, vol. 61, no. 11, pp. 1252—1258.

9. Selezneva M. S., Neusypin K. A. Development of a measurement complex with intelligent component, Measurement Techniques, December 2016, vol. 59, no. 9, pp. 916—922.

10. Kortunov V. I. et al. Integrated mini INS based on MEMS sensors for UAV control, IEEE Aerospace and Electronic Systems Magazine, 2009, vol. 24, no. 1, pp. 41—43.

11. Wang J. et al. Integration of GPS/INS/vision sensors to navigate unmanned aerial vehicles, The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2008, vol. 37, p. B1, pp. 963—969.

12. Hiliuta A., Landry R., Gagnon F. Fuzzy corrections in a GPS/INS hybrid navigation system, IEEE Transactions on Aerospace and Electronic Systems, 2004, vol. 40, no. 2 pp. 591—600.

13. Schmidt G. T., Phillips R. E. INS/GPS integration architectures, Lexington MA, Massachusetts inst of tech, 2010.

14. Chen D., Neusypin K. A., Selezneva M. S. Correction Algorithm for the Navigation System of an Autonomous Unmanned Underwater Vehicle, Sensors, 2020, vol. 20, no. 8, pp. 2365.

15. Yang G. et al. Development of the measuring complex with reduced regulator, Journal of Physics: Conference Series, IOP Publishing, 2019, vol. 1311, no. 1, p. 012037.

16. Premerlani W., Bizard P. Direction cosine matrix imu: Theory, Diy Drone: Usa, 2009, pp. 13—15.

17. Bar-Itzhack I. Y., Fegley K. A. Orthogonalization techniques of a direction cosine matrix, IEEE Transactions on Aerospace and Electronic Systems, 1969, no. 5, pp. 798—804.

18. Neusypin K. A., Selezneva M. S., Tsibizova T. Y. Diagnostics algorithms for flight vehicles navigation complex, 2018 International Russian Automation Conference (RusAutoCon), IEEE, 2018, pp. 1—6.

19. Kortunov V. I. et al. Integrated mini INS based on MEMS sensors for UAV control, IEEE Aerospace and Electronic Systems Magazine, 2009, vol. 24, no. 1, pp. 41—43.

20. Groves P. D., Mather C. J., Macaulay A. A. Demonstration of non-coherent deep INS/GPS integration for optimised signal-to-noise performance, Proceedings of the 20th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS 2007), 2007, pp. 2627—2638.


Review

For citations:


Neusypin K.A., Proletarsky A.V., Selezneva M.S. Algorithms for Complexing an Inertial Navigation System with Angular Acceleration Sensors. Mekhatronika, Avtomatizatsiya, Upravlenie. 2023;24(2):107-112. https://doi.org/10.17587/mau.24.107-112

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ISSN 1684-6427 (Print)
ISSN 2619-1253 (Online)