Exploring GNSS Crowdsourcing Feasibility: Combinations of Measurements for Modeling Smartphone and Higher End GNSS Receiver Performance.

Stefan Söderholm,Leslie Montloin,Ville V Lehtola,Michelle Koivisto

doi:10.3390/s19133018

Abstract

GNSS receiver data crowdsourcing is of interest for multiple applications, e.g., weather monitoring. The bottleneck in this technology is the quality of the GNSS receivers. Therefore, we lay out in an introductory manner the steps to estimate the performance of an arbitrary GNSS receiver via the measurement errors related to its instrumentation. Specifically, we do not need to know the position of the receiver antenna, which allows also for the assessment of smartphone GNSS receivers having integrated antennas. Moreover, the method is independent of atmospheric errors so that no ionospheric or tropospheric correction services provided by base stations are needed. Error models for performance evaluation can be calculated from receiver RINEX (receiver independent exchange format)data using only ephemeris corrections. For the results, we present the quality of different receiver grades through parametrized error models that are likely to be helpful in stochastic modeling, e.g., for Kalman filters, and in assessing GNSS receiver qualities for crowdsourcing applications. Currently, the typical positioning precision for the latest smartphone receivers is around the decimeter level, while for a professional-grade receiver, it is within a few millimeters.

Highlights

Crowdsourcing possibilities for Global Navigation Satellite Systems (GNSS) increase as the amount of GNSS receivers increases, due to an on-going trend of miniaturizing GNSS receiver components and embedding them into various devices such as mobile phones [1]
We present the quality of different receiver grades through parametrized error models that are likely to be helpful in stochastic modeling, e.g., for Kalman filters, and in assessing GNSS receiver qualities for crowdsourcing applications
The clock drift is shared with all Numerically-Controlled Oscillators (NCOs) and with all correlators that align to incoming signals

Summary

Introduction

Crowdsourcing possibilities for Global Navigation Satellite Systems (GNSS) increase as the amount of GNSS receivers increases, due to an on-going trend of miniaturizing GNSS receiver components and embedding them into various devices such as mobile phones [1]. There are already several examples of crowdsourcing possibilities for GNSS. Challenges in Arctic navigation may be tackled with a crowdsourcing approach, e.g., ice detection for threat prevention [4]. This work is part of a project aiming to improve weather monitoring in areas not yet covered by sophisticated weather measurement instruments, i.e., a project on tropospheric tomography using smartphone GNSS crowdsourcing. The number of smartphones equipped with chipset GNSS receivers has been experiencing a strong growth over the last few years. About 80% of the sold GNSS devices are installed in smartphones

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Conclusion