UWB Channel Detection and Location Algorithm Based on Likelihood Ratio Test

SUN Xiyan; LIU Jian; JI Yuanfa; LIAO Guisheng; FAN Guangwei

doi:10.11999/JEIT160484

Volume 39 Issue 3

Mar. 2017

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Article Navigation > Journal of Electronics & Information Technology > 2017 > 39(3): 590-597

SUN Xiyan, LIU Jian, JI Yuanfa, LIAO Guisheng, FAN Guangwei. UWB Channel Detection and Location Algorithm Based on Likelihood Ratio Test[J]. Journal of Electronics & Information Technology, 2017, 39(3): 590-597. doi: 10.11999/JEIT160484

Citation:

SUN Xiyan, LIU Jian, JI Yuanfa, LIAO Guisheng, FAN Guangwei. UWB Channel Detection and Location Algorithm Based on Likelihood Ratio Test[J]. Journal of Electronics & Information Technology, 2017, 39(3): 590-597. doi: 10.11999/JEIT160484

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UWB Channel Detection and Location Algorithm Based on Likelihood Ratio Test

doi: 10.11999/JEIT160484

Funds:

The National Natural Science Foundation of China (61362005,61561016), The Guangxi Natural Science Foundation Program (2013GXNSFA019004, 2014GXNSFAA118352)

Received Date: 2016-05-12
Rev Recd Date: 2016-10-17
Publish Date: 2017-03-19

Abstract

Abstract

The performance of UWB indoor positioning system is mainly affected by NLOS errors. In this paper, a channel state detection method based on channel statistics is proposed. The probability distribution function of Root Mean Square Delay Spread (RMS) and Mean Excess Delay (MED) under IEEE802.15.4a standard is modeled as standard distribution. Channel state is identified by Likelihood Ratio Test (LRT) based on KL divergence between channel instantaneous distribution and standard distribution. A localization algorithm named LRT-Chan based on LRT is proposed to improve positioning accuracy by effectively utilizing data contaminated by NLOS. Simulation results show that, LRT detection can obtain high accuracy in all UWB channels; when Anchor Nodes (ANs) with NLOS errors are not in ideal distribution, LRT-Chan algorithm can gain higher positioning accuracy.
- Likelihood ratio test,
- NLOS channel identification,
- LRT-Chan algorithm,
- KL divergence

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References(23)

References

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