BLADE: A Universal, Blind Learning Algorithm for ToA Localization in NLOS Channels

@article{PrezCruz2016BLADEAU,
  title={BLADE: A Universal, Blind Learning Algorithm for ToA Localization in NLOS Channels},
  author={Fernando P{\'e}rez-Cruz and Chih-Kuang Lin and Howard Huang},
  journal={2016 IEEE Globecom Workshops (GC Wkshps)},
  year={2016},
  pages={1-7}
}
We study wireless localization systems where multiple synchronized infrastructure devices simultaneously transmit signals whose arrival times are measured at an object of interest. The performance of these time-of-arrival (ToA) localization systems is degraded in non-line-of-sight (NLOS) channels because multipath reflections cause a positive bias in the ToA measurements. To address this major impairment, we propose an algorithm that adaptively learns the probability distribution function of… CONTINUE READING

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SHOWING 1-10 OF 18 REFERENCES

and M

  • D. Dardari, A. Conti, U. Ferner, A. Giorgetti
  • Z. Win, “Ranging with ultrawide bandwidth signals…
  • 2009
Highly Influential
3 Excerpts

ser

  • R. S. Campos, L. Lovisolo, RF Positioning
  • GNSS Technology and Applications Series. Artech…
  • 2015
1 Excerpt

An analysis of the error characteristics of two time of arrival localization techniques

  • M. Hedley T. Sathyan, M. Mallick
  • Proceedings of the 13 th International Conference…
  • 2010

OTDOA or UTDOA? Performance and implementation on lbs strategy,

  • B. Chen
  • Proceedings of the 2nd Invitational Workshop on…
  • 2010
1 Excerpt

and M

  • T. Sathyan, M. Hedley
  • Mallick, “An analysis of the error…
  • 2010

A nonlineofsight mitigation technique based on MLdetection

  • A. Urrela
  • IEEE Int . Conf . Acoustic Speech and Signal…
  • 2009

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