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State-of-the-Art Precise Point Positioning and Its Applications on Smartphone: A Review

  • Peng Liu*
  • , Honglei Qin
  • , Jun Lu
  • , Ran Liu
  • , Yong Liang Guan
  • , Chau Yuen
  • *Corresponding author for this work
  • National University of Singapore
  • Nanyang Technological University

Research output: Contribution to journal › Review article › peer-review

Abstract

Position, velocity, and timing (PVT) information is fundamental for the operation of large-scale Internet-of- Things (IoT) devices and services. Among various Global Navigation Satellite System (GNSS) positioning methods, precise point positioning (PPP) has emerged as a highly effective stand-alone solution, providing accurate and consistent performance over wide areas, and showing increasing potential for implementation on smartphones. This review focuses on smartphone-based PPP, beginning with a comparison of the positioning accuracies of primary built-in sensors commonly used for mobile localization. Key PPP processing techniques are then summarized, including preprocessing, stochastic modeling, error sources, and solution algorithms. We also introduce the classification of PPP methods and discuss their specific advantages when applied to smartphones. In addition, recent advancements over the past six years aimed at improving positioning accuracy are reviewed, including strategies for internal data integration, external data assistance, and optimization of internal models. Finally, major challenges and promising research directions in smartphone PPP are addressed, offering guidance for future development and applications of high-precision positioning in smartphones.

Original languageEnglish
Pages (from-to)13-34
Number of pages22
JournalIEEE Sensors Journal
Volume26
Issue number1
DOIs
StatePublished - Jan 2026

Keywords

  • Error sources
  • machine learning (ML)
  • precise point positioning (PPP)
  • real-time kinematic (RTK) positioning
  • smartphone positioning

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