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An Adaptive Algorithm for Multipath Mitigation in GNSS Positioning with Android Smartphones.

Lorenzo Benvenuto^1,2, Tiziano Cosso², Giorgio Delzanno¹

¹DIBRIS-Department of Informatics, Bioengineering, Robotics and Systems Engineering, University of Genoa, 16146 Genoa, Italy.

Sensors (Basel, Switzerland)

|August 12, 2022

Summary

This summary is machine-generated.

This study introduces a novel method to enhance Global Navigation Satellite System (GNSS) positioning accuracy on Android devices. The solution mitigates multipath errors using an adaptive algorithm, improving signal robustness for smartphones.

Keywords:

GNSS positioning data analysis internet of things mobile computing

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Area of Science:

Geomatics Engineering
Mobile Computing
Signal Processing

Background:

Global Navigation Satellite System (GNSS) positioning accuracy is often degraded by multipath effects, especially on mobile devices.
Smartphone antennas are susceptible to signal reflections, leading to positioning errors.

Purpose of the Study:

To develop and present a robust GNSS positioning solution for Android devices.
To mitigate the impact of multipath errors on satellite radio signals received by smartphones.

Main Methods:

An edge computing approach using a dedicated Android app for signal acquisition.
A server-based processing phase employing a modified RTKLIB open-source library.
Implementation of an adaptive algorithm based on an extended sigma-epsilon model to weight observables affected by multipath.

Main Results:

The proposed system architecture effectively integrates edge and server-side processing.
Preliminary experimental results demonstrate the potential of the adaptive algorithm in mitigating multipath effects.
The method shows promise for improving the robustness of GNSS positioning on Android devices.

Conclusions:

The presented solution offers a viable method for enhancing GNSS positioning accuracy in challenging environments.
Further research and extensive testing are warranted to fully validate the system's performance.
This approach could significantly improve location-based services relying on GNSS data from smartphones.