access icon free Model-based super-resolution time-delay estimation with sample rate consideration

Time delay estimation is of great significance in multipath propagation to recover overlapped signals and identify the channel characteristics. However, achieving a high accuracy in this purpose may pose many problems in ultra-wideband (UWB) applications. In UWB systems, capturing a signal with high sampling rates cannot readily be done; hence classical methods for time delay estimation substantially lose their precision. To overcome this challenge, the authors incorporate a robust estimation approach and supplementary sampling process in a unified algorithm to retrieve time delays from signals with low sampling rates. Toward that pursuit, a model based least squares estimator is proposed as the main approach to calculate time delays and a modified method based on multiple signal classification (MUSIC) is also presented for comparison aim. Then, the authors have developed the algorithm by embedding two additional pre-processing steps of under sampling and interpolation to achieve a higher sampling rate and a better resolution. To show the high accuracy of work, root mean square error is computed in different values of time delay. Simulation and experiment results show the considerably higher precision of the proposed algorithm in comparison with presented MUSIC type method and also previously proposed methods in literature.

Inspec keywords: signal sampling; signal classification; signal resolution; estimation theory; delay estimation; least mean squares methods; interpolation

Other keywords: model based least square estimator; model-based super-resolution time-delay estimation; robust estimation approach; ultrawideband application; multiple signal classification; multipath propagation; UWB system; overlapped signal recovery; root mean square error; MUSIC; interpolation; supplementary sampling process; sample rate consideration

Subjects: Signal processing and detection; Other topics in statistics; Interpolation and function approximation (numerical analysis); Other topics in statistics; Interpolation and function approximation (numerical analysis); Signal processing theory

References

    1. 1)
      • 7. Lagunas, E., Taponecco, L., Nájar, M., et al: ‘TOA estimation in UWB: comparison between time and frequency domain processing’, in Chatzimisios, P., Verikoukis, C., Santamaría, I., et al. (Eds): ‘Mobile lightweight wireless systems’ (Springer, Berlin, Heidelberg, 2010), pp. 506517.
    2. 2)
    3. 3)
    4. 4)
      • 8. Trees, H.L.V.: ‘Optimum array processing. Hoboken’ (Wiley, NJ, 2010).
    5. 5)
    6. 6)
    7. 7)
      • 15. Ramazan, J.S.: ‘Model-based estimation of ultrasonic echoes part I: analysis and algorithms’, IEEE Trans. Acoust. Speech Signal Process., 2012, 48, (3), pp. 787802.
    8. 8)
      • 19. Ge, F.X., Shen, D., Peng, Y., et al: ‘Super-resolution time delay estimation in multipath environments’. 2004 Ieee Wireless Communications and Networking Conf., Wcnc 2004, 2004, vol. 2, pp. 11211126.
    9. 9)
    10. 10)
    11. 11)
      • 14. Li, X., Yan, S., Ma, X.: ‘Diagonal loading least squares time delay estimation’, Chin. J. Acoust, 2012, 31, (2), pp. 165177.
    12. 12)
    13. 13)
    14. 14)
      • 11. Kay, S.M.: ‘Fundamentals of statistical signal processing, volume I: estimation theory’ (Prentice Hall PTR, 1993).
    15. 15)
    16. 16)
      • 1. Chan, Y.T.: ‘Time delay estimation in the presence of multipath propagation’, in Urban, H.G. (Ed.): ‘Adaptive Methods in Underwater Acoustics’ (Springer, Netherlands, 1985), pp. 197206.
    17. 17)
      • 13. Sachs, J.: ‘M-sequence ultra-wideband-radar: state of development and applications’. Proc. Int. of the Radar Conf., Adelaide, Australia, 2003, pp. 224229.
    18. 18)
    19. 19)
      • 2. Clifford Carter, G.: ‘Time delay estimation’, in Urban, H.G. (Ed.): ‘Adaptive methods in underwater acoustics’ (Springer, Netherlands, 1985), pp. 175196.
    20. 20)
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