Simulation Study of Rigorous Gravity Field Recovery by Combining GOCE Satellite Orbit and Gravity Gradient Data

The combined adjustment method and its data processing scheme for rigorous gravity field recovery by combining GOCE satellite orbit and gravity gradient data are discussed.The AR decorrelation filtering method for processing of colored noise,Kaula regularization method for solving the morbid normal equations,and variance component estimation(VCE) method for determining the optimal weight of SST and SGG data are studied.The results show that: Firstly,the polar gaps of SGG data will decrease the stability of the solution,and lead to a lower accuracy of low-order geopotential coefficients.Kaula regularization can be effectively used to solve the GOCE morbid equations and obtain a stable solution.Secondly,SGG colored noises degrade the total accuracy of GOCE gravity field model,especially for the low-degree of geopotential coefficients.The AR decorrelation filtering can handle the colored noise,but the solution still contains significant low-frequency errors.Thirdly,the VCE method can effectively determine the optimal weights of SST and SGG data,and it shows that the low-frequency errors caused by colored noise are effectively inhibited.Finally,the GOCE gravity field with degree of 200 is recovered from 30 days of simulated GOCE data with 5s sampling interval,and its accuracy of geoid heights and gravity anomalies between±83°latitude areas are ±3.81 cm and ±1.056 mGal,respectively.