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Analysis of limitations on recovery of gravity field based on satellite gravity gradient data 被引量:5
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作者 Xiaoyun Wan Jinhai Yu +2 位作者 Lei Liang Jiangjun Ran Richard Fiifi Annan 《Geodesy and Geodynamics》 CSCD 2021年第1期31-42,共12页
Although satellite gravity gradient data plays a great role in determining short-wavelength part of static gravity field model,accuracy of the long-wavelength part of gravity field model recovered by them are poor,whi... Although satellite gravity gradient data plays a great role in determining short-wavelength part of static gravity field model,accuracy of the long-wavelength part of gravity field model recovered by them are poor,which leads to only a few applications in time-variable gravity investigation.The reason is that some factors limit the accuracy of the gravity field recovered using gradient data,including accuracy of the gravity gradient observations,measurement bandwidth(MBW)of gradiometer,satellite inclination,etc.This paper aims at analyzing the influence of these limitations on gravity field recovery and discusses the possibility of time-variable gravity field detection by using gravity gradient observations.Firstly,for arbitrary satellite orbit inclination,we give the frequency distributions of all the components of gravity gradients(i.e.Txx;Tyy;Tzz;Txy;Txz and Tyz,).The results show that the maximum frequency of each component of the gravity gradients is the same,i.e.l=Ts(l is degree of the gravity field model,Ts is the orbital periods),and it is not influenced by the inclination of the satellite orbits.Secondly,the paper gives a theory proof to explain why only the low orders of the coefficients are influenced by polar gaps.Big polar gaps are experimented by a numerical test with inclination of 45°.Finally,considering that the measurement bandwidth can be expanded and accuracy of gradient observations can be improved by superconducting gravity gradiometer(SGG)compared to gradiometer used in Gravity field and steadystate Ocean Circulation Explorer(GOCE),the possibility of detecting time-variable gravity using gravity gradient observations is discussed.The results show that the SGG creates errors in MBW with magnitude of 0.014 m E,which is smaller than the magnitude of the time-variable gravity gradient signals(i.e.,0.02 m E)derived from Gravity Recovery and Climate Experiment(GRACE)gravity field models.This indicates the potential of SGG in time-variable gravity detection. 展开更多
关键词 Gravity gradients Gradiometer measurement bandwidth Frequency analysis polar gaps Time-variable gravity field
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Numerical Study on the Mixed Model in the GOCE Polar Gap Problem
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作者 ZOU Xiancai CAI Jianqing +1 位作者 Nico Sneeuw LI Jiancheng 《Geo-Spatial Information Science》 2011年第3期216-222,共7页
Gravity gradients acquired by the Gravity field and steady-state Ocean Circulation Explorer(GOCE) do not cover the entire earth because of its sun-synchronous orbit leaving data gaps with a radius of about 6.5° i... Gravity gradients acquired by the Gravity field and steady-state Ocean Circulation Explorer(GOCE) do not cover the entire earth because of its sun-synchronous orbit leaving data gaps with a radius of about 6.5° in the polar regions.Previous studies showed that the loss of data in the polar regions deteriorates the accuracy of the low order(or near zonal) coefficients of the earth gravity model,which is the so-called polar gap problem in geodesy.In order to find a stable solution for the earth gravity model from the GOCE gravity gradients,three models,i.e.the Gauss-Markov model,light constraint model and the mixed model,are compared and evaluated numerically with the gravity gradient simulated with the EGM2008.The comparison shows that the Best Linear Uniformly Unbiased Estimation(BLUUE) estimator of the mixed model can solve the polar gap problem as effectively as the light constraint model;furthermore,the mixed model is more rigorous in dealing with the supplementary information and leads to a better accuracy in determining the global geoid. 展开更多
关键词 Earth gravity model satellite gravity GOCE mixed model polar gap problem
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