Time-correlated Window Carrier-phase Aided GNSS Positioning Using Factor Graph Optimization for Urban Positioning

Research output: Journal article publicationJournal articleAcademic researchpeer-review

25 Citations (Scopus)

Abstract

This article proposes an improved global navigation satellite system (GNSS) positioning method that explores the time correlation between consecutive epochs of the code and carrier-phase measurements, which significantly increases the robustness against outlier measurements. Instead of relying on the time difference carrier phase which only considers two neighboring epochs using an extended Kalman filter estimator, this article proposed to employ the carrier-phase measurements inside a window, the so-called window carrier phase (WCP), to constrain the states inside a factor graph. A left null space matrix is employed to eliminate the shared unknown ambiguity variables and, therefore, correlate the associated states inside the WCP. Then, the pseudorange, Doppler, and the constructed WCP measurements are integrated simultaneously using factor graph optimization to estimate the state of the GNSS receiver. We evaluated the performance of the proposed method in two typical urban canyons in Hong Kong, achieving the mean positioning errors of 1.76 and 2.96 m, respectively, using the automobile-level GNSS receiver. Meanwhile, the effectiveness of the proposed method is further evaluated using a low-cost smartphone-level GNSS receiver, and similar improvement is also obtained when compared with several existing GNSS positioning methods.

Original languageEnglish
Pages (from-to)3370-3384
Number of pages15
JournalIEEE Transactions on Aerospace and Electronic Systems
Volume58
Issue number4
DOIs
Publication statusPublished - 1 Aug 2022

Keywords

  • Factor graph optimization (FGO)
  • global navigation satellite system (GNSS)
  • navigation
  • time difference carrier phase (TDCP)
  • urban canyons

ASJC Scopus subject areas

  • Aerospace Engineering
  • Electrical and Electronic Engineering

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