GPS Multipath Correction Model Based on Adaptive Local Mean Decomposition

  • Xusheng Chen
  • , Xianzhou Zhang*
  • , Weikai Miao
  • , Baolin Luo
  • , Yuwei Huang
  • , Xingxing Wang
  • *Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Aiming at the current situation of sifting pure frequency-modulated (FM) signal of ensemble local mean decomposition (ELMD) using hard threshold criterion, this paper proposes an improved ELMD method based on the adaptive sifting stopping criterion. The improved ELMD combined with the consecutive mean square error (CMSE) criterion, which is named as the adaptive local mean decomposition (ALMD), is used to separate the noise signal and extract the useful signal and applied to the research of GPS multipath effects. The results of numerical simulation show that compared with the traditional LMD using the hard threshold criterion and wavelet de-noising method, the de-noising method proposed in this paper is better and more stable. The usage of the proposed method, which aims to extract the multipath correction model from the coordinate residual time series, can weaken the influence of multipath effects to a certain extent, thus improve GPS positioning accuracy.

Original languageEnglish
Title of host publicationChina Satellite Navigation Conference, CSNC 2020 Proceedings
Subtitle of host publicationVolume III
EditorsJiadong Sun, Changfeng Yang, Jun Xie
PublisherSpringer
Pages252-264
Number of pages13
ISBN (Print)9789811537141
DOIs
StatePublished - 2020
Externally publishedYes
Event11th China Satellite Navigation Conference, CSNC 2020 - Chengdu, China
Duration: 22 Nov 202025 Nov 2020

Publication series

NameLecture Notes in Electrical Engineering
Volume652 LNEE
ISSN (Print)1876-1100
ISSN (Electronic)1876-1119

Conference

Conference11th China Satellite Navigation Conference, CSNC 2020
Country/TerritoryChina
CityChengdu
Period22/11/2025/11/20

Keywords

  • Consecutive mean square error
  • Ensemble local mean decomposition
  • GPS
  • Multipath effects
  • Sifting stopping criterion

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