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GNSS Observation Generation from Smartphone Android Location API: Performance of Existing Apps, Issues and

Farzaneh Zangenehnejad1, Yang Jiang1, Yang Gao1

  • 1Department of Geomatics Engineering, Schulich School of Engineering, University of Calgary, Calgary, AB T2N 1N4, Canada.

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Summary
This summary is machine-generated.

New tools improve Global Navigation Satellite System (GNSS) observation generation from smartphones. Our UofC CSV2RINEX tool enhances positioning accuracy compared to existing apps, addressing data quality concerns.

Keywords:
Geo++ RINEX logger appGnssLogger appUofC CSV2RINEX toolandroid location APIprecise point positioning (PPP)smartphone GNSS logging appssmartphone positioning

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Area of Science:

  • Geomatics Engineering
  • Satellite Navigation Systems
  • Mobile Sensing

Background:

  • Smartphones offer precise positioning crucial for location-based services (LBS).
  • Android's `android.location` API (level 24+) provides Global Navigation Satellite System (GNSS) raw measurements.
  • Existing methods require manual generation of GNSS observations (pseudorange, carrier-phase, Doppler) from API data, with reported quality issues.

Purpose of the Study:

  • To investigate algorithms for generating GNSS observations from smartphone API data.
  • To evaluate the performance of existing GNSS data logging applications.
  • To develop and assess a new tool for improved GNSS observation generation and positioning accuracy.

Main Methods:

  • Algorithm investigation for GNSS observation generation from `android.location` API.
  • Performance evaluation of Geo++RINEX logger and GnssLogger applications.
  • Development and testing of the UofC CSV2RINEX tool for converting CSV to Receiver INdependent Exchange (RINEX) files.
  • Analysis of positioning performance using generated GNSS data.

Main Results:

  • Identified quality concerns (biases, inconsistency) in GNSS observations generated by existing apps.
  • The developed UofC CSV2RINEX tool demonstrates improved positioning accuracy.
  • The study provides a comparative analysis of different GNSS data generation methods on Android.

Conclusions:

  • The UofC CSV2RINEX tool offers a more accurate solution for GNSS data processing from smartphones.
  • Addressing data quality issues in generated GNSS observations is critical for reliable positioning.
  • Further collaboration with app developers is recommended to investigate and resolve GNSS data misbehavior.