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Mitigation of Multipath Effects Based on a Robust Fractional Order Bidirectional Least Mean Square (FOBLMS) Beamforming Algorithm for GPS Receivers

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Abstract

Consideration on positioning and location services among the public has been increasing in the recent years with their applications in most of the anticipating milieus such as automobile navigation system etc. This insists for a development of high recitation global navigation satellite system such as global positioning system (GPS). Multipath effects, interference, signal jamming etc. are the major sources of error influencing the performance of the GPS receiver. Literature presents many of the multipath mitigation techniques. Among them, adaptive processing technology based beamforming algorithms appears a viable solution for multipath mitigation. The least mean square (LMS) beamforming algorithms were sensitive to dynamic environments thus affecting the accuracy of GPS. In this paper, an adaptive beamforming algorithm called fractional order bidirectional least mean square (FOBLMS) algorithm is proposed to mitigate the multipath effects and to conceal the jammer signal in a GPS receiver. The FOBLMS is an integration of the fractional calculus and bidirectional least mean square algorithm. The effectiveness of the proposed algorithm is validated using the bit error rate and experimentation gain results over the existing beamforming algorithms. Experimental results demonstrated that the performance of the proposed beamforming algorithm is better than LMS algorithm with maximal relative antenna gain of 28.92 dB, 32.84 dB for two and four element antenna arrays at − 60° and 10°, direction of arrivals respectively. The outcome of this work would be useful for developing a robust technique for multipath mitigation in GPS receivers.

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References

  1. Enge, P., & Misra, P. (1999). Special issue on global positioning system. Proceedings of the IEEE,87(1), 3–15.

    Article  Google Scholar 

  2. Yang, Y., Hatch, R. R., & Sharpe, R. T. (2004). GPS multipath mitigation in measurement domain and its applications for high accuracy navigation. In Proceedings of the ION GNSS (pp. 1–6).

  3. Xiang, F., Liao, G., Zeng, C., & Wang, W. (2013). A multipath mitigation discriminator for GPS receiver. International Journal of Electronics and Communications. https://doi.org/10.1016/j.aeue.2013.04.007.

    Article  Google Scholar 

  4. Weill, L. R. (2002). Multipath mitigation using modernized GPS signals: How good can it get? In Proceedings of ION-GPS (pp. 493–505).

  5. Mukhopadhyay, M., Sarkar, B. K., & Chakraborty, A. (2007). Augmentation of anti-jam GPS system using smart antenna with a simple DOA estimation algorithm. Proceedings of Progress in Electromagnetic Research,67, 231–249.

    Article  Google Scholar 

  6. Dong, D., Wang, M., Chen, W., & Zeng, Z. (2016). Mitigation of multipath effect in GNSS short baseline positioning by the multipath hemispherical map. Journal of Geo-Informatics,90, 255–262. https://doi.org/10.1007/s00190-015-0870-9.

    Article  Google Scholar 

  7. Garin, L., & Rousseau, J. M. (1997). Enhanced strobe correlator multipath rejection for code and carrier. In Proceedings of the tenth international technical meeting of the satellite division of the institute of navigation ION GPS-97.

  8. Xiang, F., Liao, G., Zeng, C., & Wang, W. (2013). A multipath mitigation discriminatorfor GPS receiver. International Journal of Electronics and Communications. https://doi.org/10.1016/j.aeue.2013.04.007.

    Article  Google Scholar 

  9. Moradi, R., Schuster, W., Feng, S., & Jokinen, A. (2014). The carrier-multipath observable: a new carrier-phase multipath mitigation technique. GPS Solution. https://doi.org/10.1007/s10291-014-0366-8.

    Article  Google Scholar 

  10. Bétaille, D., Cross, P. A., & Euler, H. J. (2006). Assessment and improvement of the capabilities of a window correlator to model GPS multipath phase errors. IEEE Transactions on Aerospace and Electron Systems,42(2), 707–718. https://doi.org/10.1109/TAES.2006.1642583.

    Article  Google Scholar 

  11. Bhuiyan, M., Lohan, E., & Renfors, M. (2008). Code tracking algorithms for mitigating multipath effects in fading channels for satellite-based positioning. EURASIP Journal on Advances in Signal Processing. https://doi.org/10.1155/2008/863629.

    Article  Google Scholar 

  12. Sun, L., Chen, J., Tan, S., & Chai, Z. (2014). Research on multipath limiting antenna array with fixed phase center. GPS Solution. https://doi.org/10.1007/s10291-014-0400-x.

    Article  Google Scholar 

  13. Sahmoudi, M., Amin, M. G. (2007). Optimal robust beamforming for interference and multipath mitigation in GNSS arrays. In Proceedings of IEEE international conference on acoustics, speech and signal processing. https://doi.org/10.1109/icassp.2007.366774.

  14. Yapıcı, Y., & Yılmaz, A. O. (2012). An analysis of the bidirectional LMS algorithm over fast-fading channels. IEEE Transactions on Communications,60(7), 1759–1764. https://doi.org/10.1109/tcomm.2012.050812.110116.

    Article  Google Scholar 

  15. Miller, K. S., & Ross, B. (1993). An introduction to the fractional calculus and fractional differential equations. New York: Wiley.

    MATH  Google Scholar 

  16. Daneshmand, S., Broumandan, A., Nielsen, J., & Lachapelle, G. (2013). Interference and multipath mitigation utilising a two-stage beamformer for global navigation satellite systems applications. IET Radar Sonar Navigation,7(1), 55–66. https://doi.org/10.1049/iet-rsn.2012.0027.

    Article  Google Scholar 

  17. Swathi, N., & Sasibhushana Rao, G. (2016). An adaptive filter approach for GPS multipath error estimation and mitigation. Electromagnetics and Telecommunications. https://doi.org/10.1007/978-81-322-2728-1_50.

    Article  Google Scholar 

  18. Suryasarman, P. M., & Springer, A. (2015). A comparative analysis of adaptive digital pre-distortion algorithms for multiple antenna transmitters. IEEE Transactions on Circuits and System,62(5), 1412–1420. https://doi.org/10.1109/tcsi.2015.2403034.

    Article  Google Scholar 

  19. Gui, G., Liu, N., Li, X., & Adachi, F. (2015). Low-complexity large-scale multiple-input multiple-output channel estimation using affine combination of sparse least mean square filters. IET Communication,9(17), 2168–2175. https://doi.org/10.1049/iet-com.2014.0979.

    Article  Google Scholar 

  20. Mandal, A., & Mishra, R. (2015). Design of complex non-linear adaptive equalizer in mitigating severe intersymbol interferences. Journal of Signal Processing System. https://doi.org/10.1007/s11265-015-1047-8.

    Article  Google Scholar 

  21. Ahmad, Z., Tahir, M., & Ali, I. (2013). Analysis of beamforming algorithms for antijams. In Proceedings of international seminar/workshop on direct and inverse problems of electromagnetic and acoustic wave theory, DIPED-2013 proceedings (pp. 89–96).

  22. Hongwei, Z., Baowang, L., & Juan, F. (2011). Adaptive beamforming algorithm for interference suppression in GNSS receivers. International Journal of Computer Science & Information Technology (IJCSIT),3(5), 17–28. https://doi.org/10.5121/ijcsit.2011.3502.

    Article  Google Scholar 

  23. Widrow, B., & Stearns, S. (1985). Adaptive signal processing. Upper Saddle River: Prentice Hall.

    MATH  Google Scholar 

  24. Komninakis, C., Fragouli, C., Sayed, A., & Wesel, R. (2002). Multi-input multi-output fading channel tracking and equalization using Kalman estimation. IEEE Transactions on Signal Processing,50(5), 1065–1076. https://doi.org/10.1109/78.995063.

    Article  Google Scholar 

  25. Kamatham, Y., Kinnara, B., & Kartan, M. K. (2015). Mitigation of GPS multipath using affine combination of two LMS adaptive filters. IEEE. https://doi.org/10.1109/spices.2015.7091375.

    Article  Google Scholar 

  26. Solteiro Pires, E. J., Tenreiro Machado, J. A., de Moura Oliveira, P. B., Boaventura Cunha, J., & Mendes, L. (2010). Particle swarm optimization with fractional-order velocity. Nonlinear Dynamics,61(1–2), 295–301. https://doi.org/10.1007/s11071-009-9649-y.

    Article  MATH  Google Scholar 

  27. Das, D. P., & Panda, G. (2004). Active mitigation of non-linear noise processes using a novel filtered-s LMS algorithm. IEEE Transactions on Speech and Audio Processing. https://doi.org/10.1109/tsa.2003.822741.

    Article  Google Scholar 

  28. Myrick, W. L., Zoltowski, M. D., & Goldstein, J. S. (1999). Anti-jam space-time preprocessor for GPS based on multistage nested Wiener filter. Proceedings of IEEE Conference on Military Communications. https://doi.org/10.1109/milcom.1999.822769.

    Article  Google Scholar 

  29. Zhu, Z., Gao, X., & Cao, L. (2016). Analysis on the adaptive filter based on LMS algorithm. International Journal for Light and Electron Optics. https://doi.org/10.1016/j.ijleo.2016.02.005.

    Article  Google Scholar 

  30. Bhuiyan, M. Z. H., Zhang, J., Lohan, E. S., Wang, W., & Sand, S. (2012). Analysis of multipath mitigation techniques with land mobile satellite channel model. Radio Engineering,21(4), 1067–1077.

    Google Scholar 

  31. Aruba, R., Sinha, G. R., & Rizwan, S. M. (2016). SNR and BER analysis for multiple antenna system using. Journal of Electronics and Communication Engineering,11(4), 51–56.

    Google Scholar 

  32. Lesouple, J., Robert, T., Sahmoudi, M., Tourneret, J.-Y., & Vigneau, W. (2019). Multipath mitigation for GNSS positioning in an urban environment using sparse estimation. IEEE Transactions on Intelligent Transportation Systems,20(4), 1316–1328.

    Article  Google Scholar 

  33. Su, M., Zheng, J., Yang, Y., & Wu, Q. (2018). A new multipath mitigation method based on adaptive thresholding wavelet denoising and double reference shift strategy. GPS Solutions,22, 40.

    Article  Google Scholar 

  34. Sudhakar, R., & Letitia, S. (2015). An adaptive fast block motion estimation algorithm based on cross octagonal diamond search pattern. International Journal of Applied Engineering Research,10, 11892–11898.

    Google Scholar 

  35. Sudhakar, R., & Letitia, S. (2016). An modified un-even hexagonal block search algorithm for fast motion estimation in video coding. International Journal of Research in Emerging Science and Technology,3(5), 56–61.

    Google Scholar 

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  1. Koneru Lakshmaiah Education Foundation, Vaddeswaram, Guntur, Andhra Pradesh, 522502, India

    A. L. Siridhara & D. V. Ratnam

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  1. A. L. Siridhara
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  2. D. V. Ratnam
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Correspondence to A. L. Siridhara.

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Siridhara, A.L., Ratnam, D.V. Mitigation of Multipath Effects Based on a Robust Fractional Order Bidirectional Least Mean Square (FOBLMS) Beamforming Algorithm for GPS Receivers. Wireless Pers Commun 112, 743–761 (2020). https://doi.org/10.1007/s11277-020-07071-1

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