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Improving GPS Receivers Positioning in Weak Signal Environments Based on Fuzzy SSMF-FFT and Fuzzy Kalman Filter

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Abstract

With the advent of global positioning system (GPS) and the increasing expansion of technology, improving GPS receivers positioning has attracted great attention. When the signal received by these receivers is weak, receiver functioning becomes impaired. Due to the existing noise and the presence of Doppler shift in weak signal conditions, the signal acquisition section becomes problematic and in weak signal conditions or phase lock loop (PLL), the tracking section design of noise conditions gets difficult. In case of a lock loss on the signal, the user will not be able to calculate the Doppler frequency and the system will diverge. Therefore, a robust algorithm for the GPS receiver PLL is very vital. In this paper, the squared segmented matched filter-fast Fourier transform algorithm is used to improve the acquisition of weak GPS signals with an average SNR of 15 dB. By using the matched filter, the SNR is maximized and the code phase estimation will be more accurately. Also, the use of a segmented filter before the FFT reduces the number of FFT points and therefore, the computational complexity is reduced. To calculate the number of batches and obtain the best acquisition output, in the proposed algorithm, the system becomes fuzzy. In tracking section, fractional Fourier transform (FRFT) with the PLL based on fuzzy Kalman filter (FKF) is used to reinforce it against weak signal environments. The FRFT is used for estimating frequency and acceleration, and a third-order FKF is used for designing the PLL. As a result of these changes, the RMSE of positioning is improved more than 35%.

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References

  1. Tabatabaei, A., Mosavi, M. R., Khavari, A., & Shahhoseini, H. S. (2017). Reliable urban canyon navigation solution in GPS and GLONASS integrated receiver using improved fuzzy weighted least-square method. Journal of Wireless Personal Communications, 94(4), 3181–3196.

    Google Scholar 

  2. Elango, G. A., Sudha, G. F., & Francis, B. (2017). Weak signal acquisition enhancement in software GPS receivers—Pre-filtering combined post-correlation detection approach. Applied Computing and Informatics, 13(1), 66–78.

    Google Scholar 

  3. Xia, X., Zhao, J., Long, H., Yang, G., Sun, J., & Yang, W. (2016). Fractional Fourier transform based unassisted tracking method for global navigation satellite system signal carrier with high dynamics. IET Radar, Sonar and Navigation, 10(3), 506–515.

    Google Scholar 

  4. Wang, X., Ji, X., & Feng, S. (2014). A scheme for weak GPS signal acquisition aided by SINS information. Journal of GPS Solutions, 18(2), 243–252.

    Google Scholar 

  5. Jianfeng, M., Wu, C., Yongrong, S., & Jianye, L. (2010). Low C/N0 carrier tracking loop based on optimal estimation algorithm in GPS software receivers. Chinese Journal of Aeronautics, 23(1), 109–116.

    Google Scholar 

  6. Ziedan, N. I., & Garrison, J. L. (2004). Extended Kalman filter-based tracking of weak GPS signals under high dynamic conditions. Proceedings of ION GNSS, 2004, 20–31.

    Google Scholar 

  7. Jing, S., Zhan, X., Liu, B., & Chen, M. (2016). Weak and dynamic GNSS signal tracking strategies for flight missions in the space service volume. Journal of Sensors, 16(9), 1412.

    Google Scholar 

  8. Tian, J., Yang, L., & Hang, B. (2008). A novel GNSS weak signal acquisition using wavelet denoising method. In Proceedings of the NTM ION.

  9. Shanmugam, S. K., Nielsen, J., & Lachapelle, G. (2007). Enhanced differential detection scheme for weak GPS signal acquisition. In ION GNSS (p. 14).

  10. Yanyan, Z., Lifeng, J., Wanjie, S., & Shanjun, W. (2006). Technique of Doppler compensation for phase-coded signal pulse compression. In IEEE conference on radar (pp. 1–4).

  11. Chang, L., Jun, Z., Zhu, Y., & Qingge, P. (2011). Analysis and optimization of PMF-FFT acquisition algorithm for high-dynamic GPS signal. In IEEE conference on cybernetics and intelligent systems (pp. 185–189).

  12. Lashley, M., Bevly, D. M., & Hung, J. Y. (2009). Performance analysis of vector tracking algorithms for weak GPS signals in high dynamics. IEEE Journal of Selected Topics in Signal Processing, 3(4), 661–673.

    Google Scholar 

  13. Jie, Y., Xinlong, W., & Jiaxing, J. (2010). Design and analysis for an innovative scheme of SINS/GPS ultra-tight integration. Aircraft Engineering and Aerospace Technology, 82(1), 4–14.

    Google Scholar 

  14. Miller, I., & Campbell, M. (2012). Sensitivity analysis of a tightly-coupled GPS/INS system for autonomous navigation. IEEE Transactions on Aerospace and Electronic Systems, 48(2), 1115–1135.

    Google Scholar 

  15. Savage, P. G. (2002). Analytical modeling of sensor quantization in strapdown inertial navigation error equations. Journal of Guidance, Control and Dynamics, 25(5), 833–842.

    Google Scholar 

  16. Ding, J. C., Zhao, L., Gao, S. H., Xia, L. X., & Zhang, J. L. (2011). Design and implementation of RF front-end for GPS receiver utilizing discrete components. Applied Mechanics and Materials, 44, 1330–1334.

    Google Scholar 

  17. Heiberg, A. C., Brown, T. W., Fiez, T. S., & Mayaram, K. (2011). A 250 mV, 352 muW GPS receiver RF front-end in 130 nm CMOS. IEEE Journal of Solid-State Circuits, 46(4), 938–949.

    Google Scholar 

  18. Guo, Y., Huan, H., Tao, R., & Wang, Y. (2017). Long-term integration based on two-stage differential acquisition for weak direct sequence spread spectrum signal. IET Communications, 11(6), 878–886.

    Google Scholar 

  19. Shokrollahi, A., & Mazloom-Nezhad, B. (2017). An energy-efficient clustering algorithm using fuzzy C-means and genetic fuzzy system for wireless sensor network. Journal of Circuits, Systems and Computers, 26(1), 1–22.

    Google Scholar 

  20. Luo, Y., Zhang, L., & Ruan, H. (2018). An acquisition algorithm based on FRFT for weak GNSS signals in a dynamic environment. IEEE Communications Letters, 22(6), 1212–1215.

    Google Scholar 

  21. Qaisi, A. A., & Sharadqeh, A. A. M. (2012). Signal-to-noise-ratio of signal acquisition in global navigation satellite system receiver. Computer Engineering and Intelligent Systems, 3(8), 55–59.

    Google Scholar 

  22. Rashtchi, V., & Nourazar, M. (2014). A multiprocessor NIOS II implementation of duffing oscillator array for weak signal detection. Journal of Circuits, Systems and Computers, 23(4), 1–21.

    Google Scholar 

  23. Benvenuto, N., Costa, E., & Obetti, E. (2001). Performance comparison of chip matched filter and RAKE receiver for WCDMA systems. Global Telecommunications Conference, 5, 3060–3064.

    Google Scholar 

  24. Su, X., Hao, F., Ji, Y., Zhen, W., Yu, B., & Gan, X. (2018). An unfuzzy acquisition algorithm based on matched filtering for BOC (n, n). In China satellite navigation conference (pp. 233–248).

  25. Ta, T. H., Shivaramaiah, N. C., Dempster, A. G., & Presti, L. L. (2012). Significance of cell-correlation phenomenon in GNSS matched filter acquisition engines. IEEE Transactions on Aerospace and Electronic Systems, 48(2), 1264–1286.

    Google Scholar 

  26. Roman, J. R., Rangaswamy, M., Davis, D. W., Zhang, Q., Himed, B., & Michels, J. H. (2000). Parametric adaptive matched filter for airborne radar applications. IEEE Transactions on Aerospace and Electronic Systems, 36(2), 677–692.

    Google Scholar 

  27. Ta, T. H., Pini, M., & Presti, L. L. (2014). Combined GPS L1 C/A and L2C signal acquisition architectures leveraging differential combination. IEEE Transactions on Aerospace and Electronic Systems, 50(4), 3212–3229.

    Google Scholar 

  28. Chen, S., Zhang, T., He, D., & Gao, H. (2012). NLFM-DSS signal acquisition method based on DPT and PMF-FFT. In International congress on image and signal processing (pp. 1444–1448).

  29. Liu, N., Sun, B., & Guan, C. (2013). Research on an improved PMF-FFT fast PN code acquisition algorithm. Communications and Network Scientific Research, 5(3), 266–270.

    Google Scholar 

  30. Tang, B., & Dodds, D. E. (2007). Synchronization of weak indoor GPS signals with Doppler using a segmented matched filter and accumulation. In Canadian conference on electrical and computer engineering (pp. 1531–1534).

  31. Pan, Y., Zhang, T., Zhang, G., & Luo, Z. (2016). Analysis of an improved acquisition method for high-dynamic BOC signal. Journal of Systems Engineering and Electronics, 27(6), 1157–1167.

    Google Scholar 

  32. Mosavi, M. R., Nakhaei, A., & Bagherinia, Sh. (2010). Improvement in differential GPS accuracy using Kalman filter. Journal of Aerospace Science and Technology, 7(2), 69–80.

    Google Scholar 

  33. Kim, K. H., Jee, G. I., & Song, J. H. (2008). Carrier tracking loop using the adaptive two-stage Kalman filter for high dynamic situations. International Journal of Control, Automation and Systems, 6(6), 948–953.

    Google Scholar 

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Correspondence to Mohammad-Reza Mosavi.

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Heydarnia, M., Mosavi, MR. & Rahemi, N. Improving GPS Receivers Positioning in Weak Signal Environments Based on Fuzzy SSMF-FFT and Fuzzy Kalman Filter. Wireless Pers Commun 114, 1557–1581 (2020). https://doi.org/10.1007/s11277-020-07438-4

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  • DOI: https://doi.org/10.1007/s11277-020-07438-4

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