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Adaptive Unscented Kalman Filter for Tracking GPS signals in the Case of an Unknown and Time-Varying Noise Covariance

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Abstract

A new adaptive unscented Kalman filter (AUKF) is proposed to estimate the radio navigation parameters of a GPS signal tracking system in noisy environments and on a highly dynamic object. The experimental results have shown that the proposed AUKF-based method improves the GPS tracking margin by approximately 8 and 3 dB as compared to the conventional algorithm and the KF-based tracking, respectively. At the same time, the accuracy of Doppler frequency measurements increases as well.

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REFERENCES

  1. Kaplan, E.D. and Hegarty, C.G., Understanding GPS: Principles and Applications, 2nd edition, London: Artech House, 2006.

    Google Scholar 

  2. Ward, P.W., Performance comparisons between FLL, PLL and a novel FLL-assisted-PLL carrier tracking loop under RF interference conditions, Proc. ION GPS, 1998, Nashville, TN, USA, pp. 783–795.

  3. GLONASS. Printsipy postroeniya i funktsionirovaniya GLONASS (Principles of construction and operation), Perov, A.I. and V.N. Kharisov, Eds., 4th edition, Radiotekhnika, 2010.

    Google Scholar 

  4. Mukhin, K.A., Study of a tracking system for the delay of a satellite navigation signal in conditions of narrow-band interference, Vestnik YarGU. Seriya Estestvennye i tekhnicheskiye nauki, 2014, no. 2, pp. 55–61.

  5. Hongyang, Z., Luping, Xu., Yue, J. and Xiaochen, M., A 2-step GPS carrier tracking loop for urban vehicle applications, Journal of Systems Engineering and Electronics, 2017, vol. 28, no. 5, pp. 817–826.

    Article  Google Scholar 

  6. Kanouj, M.M., Klokov, A.V., Parvatov, G.N., and Potekaev, A.E., A new approach to designing a positioning system for operation under the conditions of dynamic stress and high noise level, Russian Physics Journal, 2021, vol. 64, no. 1, pp. 156–167.

    Article  Google Scholar 

  7. Hongyang, Z., Luping, X., Bo, Y., Hua, Z., and Liyan, L., Carrier estimation method based on MLE and KF for weak GPS signals, Sensors, 2017, vol. 17, no. 7, p. 1468.

    Article  Google Scholar 

  8. Rong, Y., Keck-Voon, L., Eng-Kee, P. and Yu, M., Generalized GPS signal carrier tracking: part I-modeling and analysis, IEEE Transactions on Aerospace and Electronic Systems, 2017, vol. 53, no. 4, pp. 1781–1797.

    Article  Google Scholar 

  9. Rong, Y., Dongyang, X. and Yu, T.M., Generalized multifrequency GPS carrier tracking architecture: Design and performance analysis, IEEE Transactions on Aerospace and Electronic Systems, 2020, vol. 56, no. 4, pp. 2548–2563.

    Article  Google Scholar 

  10. Alireza, R., Demoz, G., and Dennis, M.A., Carrier loop architectures for tracking weak GPS signals, IEEE Transactions on Aerospace and Electronic Systems, 2008, vol. 44, no. 2, pp. 697–710.

    Article  Google Scholar 

  11. Zhiyong, T., Tiejun, L., and Bo, B., Research on satellite signal vector tracking based on prefilter under high dynamic conditions, Proc. 4th International Conference on Signal and Image Processing, IEEE, 2019, pp. 626–630.

  12. Zhang, X., Guo, C., and Cao, J., The study of the impact of high dynamic environment on the GPS carrier tracking, Proc. International Conference on Communications, Circuits and Systems (ICCCAS), IEEE, 2013, pp. 673–676.

  13. Xinlong, W., Xinchun, J., Shaojun, F., and Vincent, C., A high-sensitivity GPS receiver carrier-tracking loop design for high-dynamic applications, GPS Solutions, 2015, vol. 19, no. 2. pp. 225–236.

    Article  Google Scholar 

  14. Frank, V.G., Andrey, S., Maarten, U.H., and Sanjeev, G., Closed-loop sequential signal processing and open loop batch processing approaches for GPS receiver design, IEEE Journal on Selected Topics in Signal Processing, 2009, vol. 3, no. 4, pp. 571–586.

    Article  Google Scholar 

  15. Tahir, M., Presti, L. Lo, and Fantino, M., Characterizing different open loop fine frequency estimation methods for GPS receivers, Proc. ION ITM, 2012, pp. 311–355.

  16. Esther, A., A frequency domain quasi-open loop tracking loop for GPS receivers, Proc. 19th ION GPS, 2006, pp. 790–798.

  17. Robert, G.B. and Patrick, Y.C.H., Introduction to Random Signals and Applied Kalman Filtering, 4th edition, John Wiley & Sons: Hoboken, NJ, USA, 2012, p. 383.

    Google Scholar 

  18. Shavrin, V.V., Tislenko, V.I., Lebedev, V.Yu., Filimonov, V.A., and Konakov, A.S., Sigma-point Kalman filter algorithm in the problem of the GNSS signal parameters estimation in non-coherent tracking mode in spacecraft autonomous navigation equipment, Gyroscopy and Navigation, 2018, vol. 9, no. 4, pp. 255–266.

    Article  Google Scholar 

  19. Shavrin, V.V., Tislenko, V.I., Lebedev, V.Yu., Konakov, A.S., Filimonov, V.A., and Kravets, A.P., Quasioptimal estimation of GNSS signal parameters in coherent reception mode using the sigma-point Kalman filter, Gyroscopy and Navigation, 2017, vol. 8, no. 1, pp. 24–30.

    Article  Google Scholar 

  20. Yang, M., Shesheng, G., Yongmin, Z., Gaoge, H., and Aleksandar, S., Covariance matching based adaptive unscented Kalman filter for direct filtering in INS-GPS integration, Acta Astronautica, 2016, vol. 120, pp. 171–181.

    Article  Google Scholar 

  21. Yang, R., GPS signal tracking under weak signal or high dynamic environment, PhD thesis, Nanyang Technological University, Singapore, 2017.

  22. Mohammad, S.S., Dennis, M.A., and Daniel, N.A., GPS C/N 0 estimation in the presence of interference and limited quantization levels, IEEE Transactions on Aerospace and Electronic Systems, 2007, vol. 43, no. 1, pp. 227–238.

    Article  Google Scholar 

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  1. National Research Tomsk State University, Tomsk, Russia

    M. M. Kanouj & A. V. Klokov

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  1. M. M. Kanouj
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  2. A. V. Klokov
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Correspondence to M. M. Kanouj.

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Kanouj, M.M., Klokov, A.V. Adaptive Unscented Kalman Filter for Tracking GPS signals in the Case of an Unknown and Time-Varying Noise Covariance. Gyroscopy Navig. 12, 224–235 (2021). https://doi.org/10.1134/S2075108721030044

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