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Comparative analysis of recursive estimation algorithms for AUV collaborative navigation problem in the case of abnormal outliers in measurements
https://doi.org/10.17586/0021-3454-2024-67-12-1041-1051
Abstract
When solving the autonomous uninhabited underwater vehicles collaborative navigation problem, the following algorithms were compared in terms of accuracy, consistency and computational complexity: the classically constructed extended Kalman filter, the extended Kalman filter, additionally using the procedure for rejecting abnormal emissions in measurement errors and the maximum correntropy Kalman filter. The comparison was carried out under conditions of measurement noise, both Gaussian and non-Gaussian, containing pulse-type interference.
About the Author
A. M. Isaev
Concern CSRI Elektropribor; ITMO University
Russian Federation
Russian Federation
Alexey M. Isaev - JSC, Department of Advanced Navigation Systems for Navy Ffacilities, Junior Researcher
St. Petersburg
References
1. Paull L., Saeedi S., Seto M., Li H. IEEE Journal of Oceanic Engineering, 2014, no. 1(39), pp. 131–149, DOI: 10.1109/JOE.2013.2278891.
2. Stepanov O.A. Metody obrabotki navigatsionnoy izmeritel’noy informatsii (Methods of Processing Navigational Measurement Information), St. Petersburg, 2017, 196 р.
3. Koshaev D.A. Giroskopiya i Navigatsiya, 2020, no. 2(28), pp. 109–130. (in Russ.)
4. Vaulin Yu.V., Dubrovin F.S., Shcherbatyuk D.A., Shcherbatyuk A.F. Underwater Investigations and Robotics, 2019, no. 4(30), pp. 27–36. (in Russ.)
5. Baccou P., Jouvencel B., Creuze V., Rabaud C. Proc. of the MTS/ IEEE Int. Conf. and Exhibition OCEANS, 2001, vol. 3, рр. 1816–1821.
6. Zhao Y. et al. Journal of the Franklin Institute, 2015, no. 3(353), DOI:10.1016/j.jfranklin.2015.11.016.
7. Simon D. Optimal State Estimation. Kalman, H∞, and Nonlinear approaches, A John Wiley & Song Inc., 2006, 550 p.
8. Stepanov O.A. Osnovy teorii otsenivaniya s prilozheniyami k zadacham obrabotki navigatsionnoy informatsii. Ch. 1. Vvedeniye v teoriyu otsenivaniya (Fundamentals of Estimation Theory with Applications to Problems of Processing Navigational Information Part 1. Introduction to Estimation Theory), St. Petersburg, 2017, 509 р. (in Russ.)
9. Chubich V.M., Filippova E.V. Sovremennye naukoemkie tehnologii, 2018, no. 12, pp. 153–161. (in Russ.)
10. Chubich V.M., Prokofieva A.E. Proceedings of Irkutsk State Technical University, 2017, no. 12(21), pp. 123–137. (in Russ.)
11. Cinar G.T. and Príncipe J.C. The 2012 International Joint Conference on Neural Networks (IJCNN), Brisbane, QLD, Australia, 2012, pp. 1–6.
12. Izanloo R., Fakoorian S.A., Yazdi H.S., and Simon D. 2016 Annual Conference on Information Science and Systems (CISS), Princeton, NJ, USA, 2016, pp. 500–505.
13. Chen B., Liu X., Zhao H., Prıncipe J. Automatica, 2017, vol. 76, рр. 70–77.
14. Kulikova M.V. Systems & Control Letters, 2017, vol. 108, pp. 8–15.
15. Jwo D.-J., Chen Y.-L., Cho T.-S., Biswal A. Sensors, 2023, no. 23(23), pp. 9386.
16. Stepanov O.A., Litvinenko Y.A., Vasiliev V.A., Toropov A.B., Basin M.V. Gyroscopy and Navigation, 2021, no. 3(12), pp. 205–223.
17. Stepanov O.A., Isaev A.M. Giroskopiya i Navigatsiya, 2023, no. 3(31), pp. 48–65. (in Russ.)
18. Bar-Shalom Y., Li X., Kirubarajan T. Estimation with applications to tracking and navigation, NY, Wiley-Interscience, 2001, 581 p.
19. Bolotin Y.V., Bragin A.V., Gulevskii D.V. Gyroscopy and Navigation, 2021, no. 2(12), pp. 155–165.
20. Doucet A., Freitas N., Gordon N. Sequential Monte Carlo Methods in Practice, NY, Springer, 2001, 590 p.
Review
For citations:
Isaev A.M. Comparative analysis of recursive estimation algorithms for AUV collaborative navigation problem in the case of abnormal outliers in measurements. Journal of Instrument Engineering. 2024;67(12):1041-1051. (In Russ.) https://doi.org/10.17586/0021-3454-2024-67-12-1041-1051
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