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Visible Light Positioning and Navigation with Noise Mitigation Using Allan Variance

Research output: Contribution to journalJournal articlepeer-review

Published
  • Yuan Zhuang
  • Luchi Hua
  • Qin Wang
  • Yue Cao
  • Zhouzheng Gao
  • Longning Qi
  • Jun Yang
  • John Thompson
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<mark>Journal publication date</mark>1/11/2019
<mark>Journal</mark>IEEE Transactions on Vehicular Technology
Issue number11
Volume68
Number of pages13
Pages (from-to)11094 - 11106
Publication StatusPublished
Early online date24/09/19
<mark>Original language</mark>English

Abstract

Visible Light Positioning (VLP) has become an essential candidate for high-accurate positioning; however, its positioning accuracy is usually degraded by the noise in the VLP system. To solve this problem, a novel scheme of noise measurement and mitigation is proposed for VLPbased on the noise measurement from Allan Varianceand the noise mitigation from positioning algorithms such asAdaptive Least Squares (ALSQ)andExtended Kalman Filter (EKF). In this scheme, Allan Varianceis introduced for noise analysis in VLPfor the first time, which provides an efficient method for measuring the white noise in the VLPsystems. Meanwhile, we evaluate our noise reduction method under static testusing ALSQ and dynamic test using EKF. Furthermore, this article carefully discusses the relationship between positioning accuracy and Dilution of Precision (DOP) values. The preliminary field static tests demonstrate that the proposed scheme improves thepositioning accuracy by 16.5% and achieves the accuracy of 137mmwhile dynamic tests show an improvement of 60.4% and achieve the mean positioning accuracyof 153 mm.

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©2019 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.