Troposphere Monitoring Based on Crowdsourced Smartphone GNSS Data

Abstract

Global Navigation Satellite System (GNSS) is an essential tool for troposphere monitoring. Currently, GNSS meteorology depends mainly on the data from geodetic receivers of global or regional networks. However, these geodetic-grade GNSS stations are costly, and thus cannot be densely deployed, especially in less developed regions. Since the release of the Android 7 operating system in 2016, Android smartphones can be used to collect raw GNSS data. Considering that nowadays there are about 3 billion Android smartphones worldwide, a smartphone GNSS data crowdsourcing campaign was launched on March 17th 2022 as a part of the CAMALIOT project. About 5 TB of raw GNSS observations were collected around the world by more than 12 thousand users of the CAMALIOT Android application. In this contribution, we highlight the results related to the dedicated pipeline developed to process the crowdsourced smartphone GNSS data. Firstly, all the collected data were classified by a machine learning-based model to disregard observations of low quality. It was found that only about 2% of the collected data could potentially be used for troposphere delay estimation. The high-quality observations were then processed in the relative-positioning mode by forming baselines with the nearby geodetic stations. Several crowdsourced data sets were used to demonstrate that the zenith wet delays (ZWD) derived from smartphone data could achieve an accuracy of better than 10 mm. However, uncalibrated phase center variations of the smartphone antennas and multipath errors are still the main limitations to further improve the ZWD estimation. Overall, our study indicates that crowdsourced smartphone GNSS data is promising to densify the existing GNSS networks in terms of troposphere monitoring.