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An Improved Robust Interacting Multiple Model Algorithm for Underwater Acoustic Navigation

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China Satellite Navigation Conference (CSNC 2022) Proceedings

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 910))

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Abstract

In underwater acoustic long baseline navigation, the motion state of underwater vehicle is changeable and there are abnormal observations, which reduces the navigation accuracy of traditional filtering algorithm and cannot meet the demand of high precision underwater navigation. To solve this problem, this paper proposes an improved robust interacting multiple model algorithm. Firstly, the robust estimation of each model is carried out, and the equivalent variance and model probability of each model are obtained. The weight of equivalent variance is determined according to the model probability, and the mixed equivalent variance is obtained by weighted summation of equivalent variance. The mixed equivalent variance is used to replace the measurement noise variance in each model for state estimation, and the interacting robust estimation is realized. Then the model probability is updated, and the power function with faster growth rate is used to replace the matching model probability to realize the model probability correction. Finally, the final state estimation value and its covariance matrix are obtained by weighted summation of the results of the interacting robust estimation of each model according to the revised model probability, so as to improve the navigation accuracy and stability of underwater vehicles. By processing simulation and measured data, the results show that compared with Kalman filter, interactive multi-model and robust interactive multi-model, in the simulation data, the navigation error of the proposed method is reduced by 64.18%, 26.35% and 10.61%, respectively; in the measured data, the navigation accuracy of this method is improved by 31.79%, 14.76% and 14.93% respectively, and the navigation accuracy reaches 3.7687 m in 3 km × 3 km. Compared with the traditional filtering algorithm, the improved robust interacting multiple model algorithm can significantly improve the navigation accuracy and stability of underwater vehicles.

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Acknowledgements

The study is funded by National Key Research and Development Program of China (2020YFB0505800 and 2020YFB0505804), Wenhai Program of the S&T Fund of Shandong Province for Pilot National Laboratory for Marine Science and Technology (Qingdao) (NO. 2021WHZZB1004), Open foundation of State Key Laboratory of Geo-information Engineering (SKLGIE2019-Z-2-2), Foundation of Key Laboratory of Marine Environmental Survey Technology and Application, Ministry of Natural Resources, China (MESTA-2020-B013).

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Correspondence to Tianhe Xu .

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Shu, J., Xu, T., Wang, J., Liu, Y., Li, M. (2022). An Improved Robust Interacting Multiple Model Algorithm for Underwater Acoustic Navigation. In: Yang, C., Xie, J. (eds) China Satellite Navigation Conference (CSNC 2022) Proceedings. Lecture Notes in Electrical Engineering, vol 910. Springer, Singapore. https://doi.org/10.1007/978-981-19-2576-4_45

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  • DOI: https://doi.org/10.1007/978-981-19-2576-4_45

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-19-2575-7

  • Online ISBN: 978-981-19-2576-4

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