A refined acceleration approach for deriving monthly gravity field solutions from K-band range-acceleration observations

Abstract This paper describes a refined version of the point acceleration approach, referred to as the refined acceleration approach, which makes use of K-band range-acceleration observations to derive high-precision monthly gravity field solutions. For overcoming shortcomings of the conventional approach, several refinements are made as follows: (1) The interepoch correlated errors caused by numerical differentiation are decorrelated by a decorrelation operator. (2) The satellite velocity is transformed into a function of satellite positions and dynamic parameters. (3) The effect of satellite position error is taken into consideration while building the range-acceleration observational equation. (4) An autoregression model is used for modelling the high-frequency error of K-band range-acceleration observations. Applying the proposed approach, Gravity Recovery and Climate Experiment Follow-on, abbr. GFO, observation data spanning the period from 2019 January to 2022 December were processed and a time-series of monthly gravity field solutions was derived and referred to as SSM-ACC-GFO where the SSM is the acronym of the School of Survey and Mapping, the ACC underlines the usage of range-acceleration and the GFO shows the data source. This time-series is comprehensively compared with three official time-series, that is, CSR RL06, JPL RL06 and GFZ RL06, both in spectral and spatial domain. Comparison results demonstrate that SSM-ACC-GFO performs comparably with JPL RL06 and GFZ RL06 indicating that the refined acceleration approach has the ability of deriving high-precision monthly gravity field solutions.