Adaptive Unscented Kalman Filter for Tracking GPS Signals in the Case of an Unknown and Time-Varying
https://doi.org/10.17285/0869-7035.0069
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 AUKFbased method improves the GPS tracking margin by approximately 8 dB 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.
About the Authors
М.М. Kanouj
National Research Tomsk State University, Tomsk, Russia
Russian Federation
Russian Federation
А. V Klokov
National Research Tomsk State University
Russian Federation
Russian Federation
References
1. Kaplan, E.D., Hegarty, C.G., Understanding GPS: Principles and Applications, 2nd ed, London: Artech House, 2006.
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. ГЛОНАСС. Принципы построения и функционирования / под ред. А.И. Перова, В.Н. Харисова. Изд. 4-е, перераб. и доп. М.: Радиотехника, 2010. 800 с.
4. Мухин К.А. Исследование системы слежения за задержкой спутникового навигационного сигнала в условиях узкополосной помехи // Вестник ЯрГУ. Серия «Естественные и технические науки». 2014. № 2. С. 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.
6. Кануж М.М., Клоков А.В., Парватов Г.Н., Потекаев А.Е. Новый подход в создании GPS систем позиционирования в динамических условиях приема с высоким уровнем шумов // Физика. 2021. Т 64. № 7. С. 134–144.
7. Hongyang, Z., Luping, X., Bo, Y., Hua, Z. and Liyan, L., Carrier estimation method based on MLE and KF for weak GNSS signals, Sensors, 2017, vol. 17, no. 7, p. 1468.
8. Rong, Y., Keck-Voon, L., Eng-Kee, P. and Yu, M., Generalized GNSS signal carrier tracking: part I-modeling and analysis, IEEE Transactions on aerospace and electronic systems, 2017, vol. 53, no. 4, pp. 1781–1797.
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.
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.
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.
14. Frank, V.G., Andrey, S., Maarten, U.H., and Sanjeev, G., Closed-loop sequential signal processing and open loop batch processing approaches for GNSS receiver design, IEEE Journal on Selected Topics in Signal Processing, 2009, vol. 3, no. 4, pp. 571–586.
15. Tahir, M., Presti, L. Lo and Fantino, M., Characterizing different open loop fine frequency estimation methods for GNSS receivers, Proc. ION ITM, 2012, pp. 311–355.
16. Esther, A., A frequency domain quasi-open loop tracking loop for GNSS receivers, Proc. 19th ION GNSS, 2006, pp. 790–798.
17. Robert, G.B. and Patrick, Y.C.H., Introduction to random signals and applied Kalman filtering, 4th ed, John Wiley & Sons: Hoboken, NJ, USA, 2012, p. 383.
18. Шаврин В.В., Филимонов В.А., Лебедев В.Ю., Тисленко В.И., Конаков А.С. Сигма-точечный алгоритм фильтра Калмана в задаче оценки параметров сигналов ГНСС в некогерентном режиме слежения в аппаратуре автономной навигации космических аппаратов // Гироскопия и навигация. 2018, № 3 (102). C. 23–39.
19. Шаврин В.В., Филимонов В.А., Лебедев В.Ю., Тисленко В.И., Кравец А.П., Конаков А.С. Квазиоптимальная оценка параметров сигналов ГНСС в режиме когерентного приема с использованием алгоритма сигма-точечного фильтра Калмана // Гироскопия и навигация. 2016. № 3 (94). C. 26–37.
20. Yang, M., Shesheng, G., Yongmin, Z., Gaoge, H. and Aleksandar, S., Covariance matching based adaptive unscented Kalman filter for direct filtering in INS-GNSS integration, Acta Astronautica, 2016, vol. 120, pp. 171–181.
21. Yang, R, GNSS 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/N0 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.
Review
For citations:
Kanouj М., Klokov А.V. Adaptive Unscented Kalman Filter for Tracking GPS Signals in the Case of an Unknown and Time-Varying. Giroskopiya i Navigatsiya. 2021;29(3):34-51. (In Russ.) https://doi.org/10.17285/0869-7035.0069
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