New publication by Pan et al. (2024)
"Determination of high-precision tropospheric delays using crowdsourced smartphone GNSS data" by Pan et al. (2024)
The Global Navigation Satellite System (GNSS) is an essential tool for tropospheric monitoring. Currently, GNSS meteorology relies primarily on geodetic-grade stations. However, such stations are too costly to be densely deployed, which limits the contribution of GNSS to tropospheric monitoring.
To explore the potential of crowdsourced smartphone GNSS data for tropospheric monitoring, the chair of Space Geodesy, in collaboration with International Institute for Applied Systems Analysis (IIASA), launched the Application of Machine Learning Technology for GNSS IoT Data Fusion (CAMALIOT) crowdsourcing campaign in 2022. This paper proposed a dedicated data processing pipeline to process the large volume of GNSS data, including machine learning (ML)-based data selection and Precise Point Positioning (PPP)-based Zenith Total Delay (ZTD) estimation. It demonstrates that high-precision ZTD could be derived from crowdsourced smartphone GNSS data and also reveals success factors and current limitations.
Find the full article here:
external page https://doi.org/10.5194/amt-17-4303-2024
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The CAMALIOT app used for smartphone raw GNSS data collection. -
ZTD estimation errors using the crowdsourced smartphone data in Germany.
Reference
Pan, Y., Kłopotek, G., Crocetti, L., Weinacker, R., Sturn, T., See, L., Dick, G., Möller, G., Rothacher, M., McCallum, I., Navarro, V., and Soja, B.: Determination of high-precision tropospheric delays using crowdsourced smartphone GNSS data, Atmos. Meas. Tech., 17, 4303–4316, external page https://doi.org/10.5194/amt-17-4303-2024, 2024.