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Reliable Urban Canyon Navigation Solution in GPS and GLONASS Integrated Receiver Using Improved Fuzzy Weighted Least-Square Method

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Abstract

Global Positioning System encounters many problems in urban canyons and hard environments because of obstacles that decrease the number of visible satellites in receiver view. So, integration with other satellite-based navigation systems such as Russian Global Navigation Satellite System is utilized in new receivers. Least square as the popular and usual method typically used for navigation solution associates all satellite information with the same weights. However, the satellite impacts in reliability and accuracy of the receiver outputs are different in real condition and can be weighted by intelligent factors. In this paper, an improved fuzzy-weighted least square method is proposed which weights the satellite based on the satellite effect on dilution of precision, elevation angle and a defined constellation factor. Experimental results show that the proposed method can calculate 2D position more reliable and accurate than other popular weighted least square methods. This improvement is more than 57.23 % in a defined figure of merit.

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References

  1. Marais, J., Nahimana, D. F., Viandier, N., & Duflos, E. (2013). GNSS accuracy enhancement based on pseudo range error estimation in an urban propagation environment. Journal of Expert Systems with Applications, 40(15), 5956–5964.

    Article  Google Scholar 

  2. Kuusniemi, H.,& Lachapelle, G. (2004). “GNSS Signal Reliability Testing in Urban and Indoor Environments”, Proceedings of ION NTM Conference (pp. 1–15).

  3. Cai, C., & Gao, Y. (2009). “A combined GPS/GLONASS navigation algorithm for use with limited satellite visibility”. The Journal of Navigation, 62(4), 671–685.

    Article  Google Scholar 

  4. Angrisano, A., Gaglione, S., & Gioia, C. (2013). Performance assessment of GPS/GLONASS single point positioning in an urban environment. Journal of Acta Geodaetica et Geophysica, 48(2), 149–161.

    Article  Google Scholar 

  5. Jokinen, A., Feng, S., Milner, C., Schuster, W., & Ochieng, W. (2011). “Precise Point Positioning and Integrity Monitoring with GPS and GLONASS”, European Navigation Conference (pp.1–12).

  6. Melgard, T., Vigen, E.,& Orpen, O.(2009). “Advantages of Combined GPS and GLONASS PPP -Experiences based on G2, A New Service from Fugro”, 13th IAIN World Congress (pp. 1–7).

  7. Azami, H., Mosavi, M. R., & Sanei, S. (2013). Classification of GPS satellites using improved back propagation training algorithms. Journal of Wireless Personal Communications, 71(2), 789–803.

    Article  Google Scholar 

  8. Saraf, M., Mohammadi, K., & Mosavi, M. R. (2011). Bayesian framework on GPS GDOP classification. Journal of Computers and Electrical Engineering, 37, 1009–1018.

    Article  Google Scholar 

  9. Mosavi, M. R., Azarshahi, S., EmamGholipour, I., & Abedi, A. A. (2014). Least squares techniques for gps receivers positioning filter using pseudorange and carrier phase measurements. Iranian Journal of Electrical and Electronic Engineering, 10(1), 18–26.

    Google Scholar 

  10. Tay, S., & Marais, J. (2013).“Weighting Models for GPS Pseudorange Observations for Land Transportation in Urban Canyons”, 6th European Workshop on GNSS Signals and Signal Processing (pp. 1–4).

  11. Rahemi, N., Mosavi, M. R., Abedi, A. A., & Mirzakuchaki, S. (2014). Accurate solution of navigation equations in GPS receivers for very high velocities using pseudorange measurements. Journal of Advances in Aerospace Engineering, 2014(2014), 1–8.

    Article  Google Scholar 

  12. Mosavi, M. R. (2004). “Fuzzy Point Averaging of the GPS Position Components”, 3th Annual Conference and Exhibition on Geographical Information Technology and Applications.

  13. Groves, P. D. (2011). Shadow matching: A new GNSS positioning technique for urban canyons. The Journal of Navigation, 64, 417–430.

    Article  Google Scholar 

  14. Wang, K., & Zhao, L. (2014). “GPS/INS Integrated Urban Navigation System Based on Vehicle Motion Detection”, IEEE Chinese Guidance, Navigation and Control Conference (CGNCC) (pp. 667–670).

  15. Won, D. H., Lee, E., Heo, M., Sung, S., Lee, J., & Lee, Y. J. (2014). GNSS integration with vision-based navigation for low GNSS visibility conditions. Journal of GPS Solutions, 18(2), 177–187.

    Article  Google Scholar 

  16. Aumayer, B. M., Petovello, M. G.,& Lachapelle, G. (2014).“Development of a Tightly Coupled Vision/GNSS System”, the 27th International Technical Meeting of The Satellite Division of the Institute of Navigation (pp. 2202–2211).

  17. Mosavi, M. R., & EmamGolipour, I. (2013). De-noising of GPS receivers positioning data using wavelet transform and bilateral filtering. Journal of Wireless Personal Communications, 71(3), 2295–2312.

    Article  Google Scholar 

  18. Li, P., & Zhang, X. (2014). Integrating GPS and GLONASS to accelerate convergence and initialization times of precise point positioning. Journal of GPS Solutions, 18(3), 461–471.

    Article  Google Scholar 

  19. Blanch, J., Walter, T., & Enge, P. (2012). Satellite navigation for aviation in 2025. Proceedings of the IEEE, 100(No.Special Centennial Issue), 1821–1830.

    Article  Google Scholar 

  20. Wang, J., & Rizos, C. (2001). GPS and GLONASS integration: Modeling and ambiguity resolution issues. Journal of GPS Solutions, 5(1), 55–64.

    Article  Google Scholar 

  21. Walter, T., Blanch, J., Choi, M. J., Reid, T., & Enge, P. (2013).“Incorporating GLONASS into Aviation RAIM Receivers”, the International Technical Meeting of the ION (pp. 239–249).

  22. Mosavi, M. R., & Rahemi, N. (2015). Positioning performance analysis using RWLS algorithm based on variance estimation methods. Journal of Aerospace Science and Technology, 42, 88–96.

    Article  Google Scholar 

  23. Li, J., & Wu, M. (2009). “The Improvement of Positioning Accuracy with Weighted Least Square Based on SNR”, IEEE Conference on Wireless Communications, Networking and Mobile Computing (pp. 1−4).

  24. Rahemi, N., Mosavi, M. R., Abedi, A. A., & Mirzakuchaki, S. (2014). Accurate solution of navigation equations in GPS receivers for very high velocities using pseudorange measurements. Journal of Advances in Aerospace Engineering, 2014, 1–8.

    Article  Google Scholar 

  25. Yang, Q., & Sun, J. (2007). “A Location Method for Autonomous Vehicle based on Integrated GPS/INS”, IEEE Conference on Vehicular Electronics and Safety (pp. 1–4).

  26. Lin, C. C., Wang, L. S., Chang, F. R., & Chen, C. C. (2006). Use of residual DOP and genetic algorithm in weighted-least-square GPS positioning”, the National Technical Meeting of ION (pp. 508–514).

  27. Borre, K., Akos, D. M., Bertelsen, N., Rinder, P., & Jensen, S. H. (2007). A software-defined GPS and Galileo receiver: A single-frequency approach, applied and numerical harmonic analysis. Boston: Birkhauser.

    MATH  Google Scholar 

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Authors and Affiliations

  1. Department of Electrical Engineering, Iran University of Science and Technology, Narmak, Tehran, 16846-13114, Iran

    A. Tabatabaei, M. R. Mosavi, A. Khavari & H. S. Shahhoseini

Authors
  1. A. Tabatabaei
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  2. M. R. Mosavi
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  3. A. Khavari
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  4. H. S. Shahhoseini
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Correspondence to M. R. Mosavi.

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Tabatabaei, A., Mosavi, M.R., Khavari, A. et al. Reliable Urban Canyon Navigation Solution in GPS and GLONASS Integrated Receiver Using Improved Fuzzy Weighted Least-Square Method. Wireless Pers Commun 94, 3181–3196 (2017). https://doi.org/10.1007/s11277-016-3771-1

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  • DOI: https://doi.org/10.1007/s11277-016-3771-1

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