Identifying healthy urban zones for GNSS-based tropospheric delay estimation using 3D ray-tracing

Abstract

Global Navigation Satellite System (GNSS) based tropospheric sensing offers great potential for high-resolution weather forecasting, especially in dense cities where conventional infrastructure is limited. However, Zenith Tropospheric Delay (ZTD) estimation is challenged by multipath interference and non-line-of-sight (NLOS) conditions. This study presents a ray-tracing–assisted method to identify “healthy zones” for robust ZTD estimation. Using Hong Kong as a case study, we simulate GNSS signal propagation with 3D buildings to map LOS satellite availability. Locations with at least four clean LOS satellites are identified as healthy zones suitable for crowdsourced data collection. We further propose a Ray-Tracing-Assisted PPP framework that excludes multipath and NLOS-contaminated observations, significantly reducing ZTD bias and variability. This approach demonstrates the potential to transform urban crowdsourced GNSS data into reliable tropospheric observations for real-time atmospheric sensing.