Spatial and temporal characteristics of optimum process noise values of tropospheric parameters for kinematic analysis of Global Navigation Satellite System (GNSS) sites in Japan 6. Geodesy

Kinematic analysis of Global Navigation Satellite System (GNSS) data is useful for the extraction of crustal deformation phenomena occurring over short timescales ranging from seconds to 1 day, such as coseismic and postseismic deformation following large earthquakes. However, a fundamental challenge in kinematic GNSS analysis is to separate unknown parameters, such as site coordinate and tropospheric parameters, due to the strong correlation between them. In this study, we assessed the spatial and temporal characteristics of process noise for unknown tropospheric parameters such as zenith wet tropospheric delay and tropospheric gradient by means of kinematic precise point positioning analysis using Kalman filtering across the Japanese nationwide continuous GNSS network. We estimated kinematic site coordinate time series under different process noise combinations of zenith wet tropospheric delay and tropospheric gradient. The spatial distribution of the optimum process noise value for the zenith wet tropospheric parameter with vertical site coordinate time series clearly showed regional characteristics. In comparison with the wet tropospheric parameter, the spatial characteristics of the tropospheric gradient parameter are less well defined within the scale of the GNSS network. The temporal characteristics of the optimum process noise parameters for each site coordinate component at specific sites indicated a clear annual pattern in the tropospheric gradient parameter for the horizontal components. Finally, we assessed the effects on the kinematic GNSS site coordinate time series of optimizing tropospheric parameter process noise. Compared with recommended process noise values from previous studies, the use of estimated "common" optimum process noise values improved the standard deviation of coordinate time series for the majority of stations. These results clearly indicate that the use of appropriate process noise values is important for kinematic GNSS analysis.[Figure not available: see fulltext.]