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Abstract

Global Navigation Satellite Systems (GNSS) have shown their superiority in monitoring atmosphere variations over years. With the reduced size and cost of GNSS devices, the number of GNSS receivers deployed on the ground significantly increased worldwide. The high density of GNSS receivers enables researchers to monitor the dynamics of atmospheric conditions at the global scale for research purposes., for example, precipitable water vapor (PWV) research in the troposphere. Accurate estimation of water vapor changes in lower atmosphere is indispensable for numerical research of climate change, and weather and storm prediction. However, there is one intrinsic shortcoming in the quality control procedure of GNSS-based PWV estimation which is the lack of non-reference value to control PWV estimation quality. As a result, GNSS system is not able to complete the self-quality control to quantify the impact of measurement outliers on GNSS based PWV estimation. To address this issue, the quality control process that is commonly utilized in precise point positioning (PPP) is proposed here. With the introduction of outlier identification, optimal estimation, least squares method and Kalman Filter, the GNSS-based PWV estimation could achieve its self-contained quality control. This research reviews the GNSS-PWV estimation quality control methods developed recently, and discusses existing problems and potential solutions.