The Received Signal Characteristics-Based TOA Estimation in UWB Dense Multipath Channels

Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 246)

Abstract

In impulse radio ultra wideband (IR-UWB) dense multipath environment, the time of arrival (TOA) based on energy detection (ED) estimation algorithms are usually used as the ranging methods, in which the signal’s first path (FP) detection is very challenging. In ED receiver, threshold-crossing (TC) algorithms are used frequently. The choice of threshold becomes a key part of TC algorithms, or else the false detection probability will be high. The paper sets the threshold according to the skewness and the maximum slope of the received signal, and then because of the fixity of the FP and the randomness of TC noise samples, detects the FP by calculating the frequencies of TC energy samples in certain frames. The performance of several approaches is compared via Monte Carlo simulations using the CM3 channel model of the standard IEEE 802.15.4a. Simulation results show that the TOA estimation algorithm in the paper outperforms others.

Keywords

UWB Time of arrival Energy receiver Threshold 

Notes

Acknowledgments

This work was supported by the special fund of Chongqing key laboratory (CSTC) and by the project of Chongqing Municipal Education Commission (Kjzh11206) and National Science & Technology Major Program (2011ZX03006-003 (7)) and by Fundamental and Frontier Research Project of Chongqing (cstc2013jcyjA40034).

References

  1. 1.
    D’Amico AA et al (2008) Energy-based TOA estimation. IEEE Trans Commun 7(3):838–847. doi: 10. 1109/TWC. 2008. 060545 Google Scholar
  2. 2.
    Stoica L et al (2006) A low-complexity noncoherent IR-UWB transceiver architecture with TOA estimation. IEEE Trans Microw Theory Tech 54(4):1637–1646. doi: 10. 1109/TMTT. 2006. 872056 CrossRefGoogle Scholar
  3. 3.
    Gezici S et al (2005) Localization via ultra-wideband radios: a look at positioning aspects for future sensor networks. IEEE Signal Processing Mag 22(4):70–84. doi: 10. 1109/MSP. 2005. 1458289 CrossRefGoogle Scholar
  4. 4.
    Soganci H et al (2011) Accurate positioning in ultra-wideband systems. IEEE Wireless Commun 18(2):19–27. doi: 10. 1109/MWC. 2011. 5751292 CrossRefGoogle Scholar
  5. 5.
    Dardari D et al (2008) Threshold-based time of arrival estimators in UWB dense multipath channels. IEEE Trans Commun 56(8):1366–1378. doi: 10. 1109/TCOMM. 2008. 050551 CrossRefGoogle Scholar
  6. 6.
    Maali A et al (2009) Adaptive CA-CEAR threshold for Non-coherent IR-UWB energy detector receivers. IEEE Commun Lett 13(12):959–961. doi: 10. 1109/LCOMM. 2009. 12. 091579 CrossRefGoogle Scholar
  7. 7.
    Hao Z et al (2012) Threshold selection for TOA estimation based on skewness and slope in ultra-wideband sensor networks. J Netw 7(7):1038–1045. doi: 10.4304/JNW.7.7 Google Scholar
  8. 8.
    Guvenc I, Sahinoglu Z (2005) Threshold selection for UWB TOA estimation based on kurtosis analysis. IEEE Commun Lett 9(12):1025–1027. doi: 10. 1109/LCOMM. 2005. 1576576 CrossRefGoogle Scholar
  9. 9.
    Chi X, Law CL (2008) Delay-dependent threshold selection for UWB TOA estimation. IEEE Commun Lett 12(5):380–382. doi: 10. 1109/LCOMM. 2008. 080015 CrossRefGoogle Scholar
  10. 10.
    Wenyan L et al (2012) TOA estimation in IR UWB ranging with energy detection receiver using received signal characteristics. IEEE Commun Lett 16(5):738–741. doi: 10. 1109/LCOMM. 2012. 030912. 112445 CrossRefGoogle Scholar
  11. 11.
    Feng W et al (2011) Weighted energy detection for non-coherent ultra-wideband receiver design. IEEE Trans Wireless Commun 10(2):710–720. doi: 10. 1109/TWC. 2010. 120310. 101390 CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  1. 1.Chongqing Key Lab of Mobile Communications TechnologyChongqing University of Posts and TelecommunicationsChongqingP. R. China

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