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An Adaptive Weighted Model Considering Multipath for Precise Point Positioning

  • Qieqie Zhang
  • , Rui Chen
  • , Long Zhao*
  • *Corresponding author for this work
  • Beihang University

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

Abstract

In an urban scenario, multipath is one of the main error sources that affects positioning performance. In order to mitigate the impact of multipath on the positioning results, an adaptive weighting model considering multipath is proposed in this paper. In this method, the pseudorange multipath observation model is used to obtain the pseudorange multipath estimation, and the multipath is regarded as a disturbance item added to the observation noise. The normal distribution hypothesis test is performed on the multipath estimation, so as to detect the multipath, and reduce the weight of pseudorange observations containing the multipath. The effectiveness of the proposed method is verified by both static and kinematic tests. The results show that the proposed method can further improve the positioning accuracy and stability of precise point positioning.

Original languageEnglish
Title of host publicationProceedings of 2021 Chinese Intelligent Systems Conference - Volume II
EditorsYingmin Jia, Weicun Zhang, Yongling Fu, Zhiyuan Yu, Song Zheng
PublisherSpringer Science and Business Media Deutschland GmbH
Pages498-507
Number of pages10
ISBN (Print)9789811663239
DOIs
StatePublished - 2022
Event17th Chinese Intelligent Systems Conference, CISC 2021 - Fuzhou, China
Duration: 16 Oct 202117 Oct 2021

Publication series

NameLecture Notes in Electrical Engineering
Volume804 LNEE
ISSN (Print)1876-1100
ISSN (Electronic)1876-1119

Conference

Conference17th Chinese Intelligent Systems Conference, CISC 2021
Country/TerritoryChina
CityFuzhou
Period16/10/2117/10/21

Keywords

  • Adaptive weighting model
  • Multipath detection and mitigation
  • Precise point positioning

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