Evaluating Dual-Frequency, Multi-Constellation GNSS Performance of Modern Smartphones for Atmospheric Monitoring Across Mountainous and Urban Areas

Recent advancements in Global Navigation Satellite System (GNSS) technology have enabled the integration of dual-frequency, multi-constellation capabilities into modern smartphones, significantly enhancing their potential for various applications beyond traditional navigation. One promising application is atmospheric monitoring, where GNSS-based observations—such as those of atmospheric water vapor—are used to improve weather forecasting, track climatic changes, and provide critical insights for environmental studies. However, the use of smartphones for GNSS-based atmospheric monitoring faces challenges, particularly in terms of signal reliability and accuracy, which can vary significantly depending on the surrounding environment. The authors aim to evaluate the performance of dual-frequency, multi-constellation GNSS capabilities in modern smartphones for atmospheric monitoring across both urban and rural environments, providing a comprehensive analysis of their accuracy, reliability, and potential limitations. Towards that, this paper presents a preliminary study on the feasibility of estimating the Zenith Tropospheric Delay at different environments and elevation through the collection of GNSS data from a flagship high-end Android smartphone equipped with dual-frequency (L1 and L5) and multi-constellation (GPS, Galileo, GLONASS, and BeiDou) capabilities and pitching it against a high performing commercial low-cost GNSS receiver. Preliminary results suggest that modern smartphones equipped with dual-frequency, multi-constellation GNSS are capable of promising accuracy for atmospheric monitoring, particularly in rural or high elevation areas with minimal obstructions. Our findings indicate that such smartphones have the potential to serve as low-cost, accessible tools for atmospheric monitoring, especially in open-sky rural environments where conditions are more favorable.