The Earth's Field Model Recovery On The Basis Of Satellite-to-Satellite Tracking Missions

The global coverage, high accuracy space gravity data, such as precision orbits andK-Band observables of GRACE, and so on can be provided by satellite-to-satellitetracking missions (e.g. CHAMP, GRACE), which contain abundant Earth gravity fieldinformation, specially K-Band observables of GRACE. Nowadays, the orbit of LEOsatellite has been determined with an accuracy of a few cm (approximately 2cm), therefore the K-band observables will be the main carrier of Earth gravity fieldinformation. How to recover the gravity model based on the K-Band observables willbecome one of the hotspots in the world, and its results have a wide applicationforeground in modern geodesy, geophysics, oceanography, geodynamics, and so on.The gravity model recovery on the basis of satellite-to-satellite tracking data ismainly discussed in this dissertation, and the main work and contributions aresummarized as following:(1) The development history, domestic and overseas study present state andsignificance of satellite gravity technology are presented. A few methods forrecovering the Earth gravity field are discussed and their advantages anddisadvantages are also analyzed.(2) The time system, coordinate system and the various perturbation force models ofsatellite-to-satellite tracking measurements are introduced in detail, the basis theoryand algorithm of satellite gravity measurements, and the calculation of partialderivative are also given in this dissertation. We analyzed the effect of initial stateerror of LEO satellite on the Earth gravity model recovery using the precision orbits.In the dissertation, simulated results also showed if the other measurement errors (e.g.accelerometer errors) are not considered, the arc length of two hours should be used.(3) The preprocessing approaches for CHAMP and GRACE observables are discussedin detail, three cases of attitude data gap are analyzed and a quadratic interpolationmethod is proposed to fill the attitude data gap, The results can satisfy the requirementaccuracy in case of data gap less than 40 epochs.(4) The scale factor and bias parameters of CHAMP satellite accelerometer data arere-calibrated based on the dynamical method, the results show that the calibrationparameters which are consistent with the results provided by GFZ are variational, andthe change scope of those parameters from one day data is smaller than that from an hour. The accuracy of Earth gravity field based on the calibrated accelerometer data ishigher, so it is necessary to do the re-calibrating work.(5) The GRASTAR developed independently with Visual C++ has been introduced, which is used for processing satellite gravity data, including CHAMP and GRACEdata, and this software can be easily transplanted and maintained.(6) The dynamical method for recovering gravity field model based on the precisionorbits and accelerometer data of CHAMP is discussed and the mathematical algorithmis enduced, in which the accelerometer scale and bias, the satellite's initial state vectorand the model coefficients are estimated simultaneously. The gravity field modelTJCHAMP01S up to degree/order 50 has been computed with this algorithm from the120-day CHAMP data including dynamical orbits and accelerometer data, and themodel is validated using various criteria. The results show that the modelTJCHAMP01S is more accurate than EGM96 and EIGEN-1S model of the samedegree and order, and is close to the model EIGEN-2. The geoid height differences ofTJCHAMP01S, EIGEN-2 with respect to EIGEN-CG01C are 4.4cm and 3.3cm up todegree/order 30 in our country.(7) The gravity field model TJGRACE01 S_OR up to degree/order 36 has been computedfrom the 26-day GRACE data including dynamical orbits and accelerometer data, andthe model is validated using various criteria. The results show that the modelTJGRACE01S OR is more accurate than EGM96 and EIGEN-2 model of the samedegree and order, and is close to the model EIGEN-CHAMP03S up to degree/order 20.(8) The dynamical method for recovering gravity field model based on the range rateand accelerometer data of GRACE is discussed and the mathematical algorithm isenduced, in which the accelerometer scale and bias, the satellite's initial relativevelocity vector and the model coefficients are estimated simultaneously. The gravityfield model TJGRACE01S up to degree/order 60 has been computed with this algorithmfrom the 31-day GRACE data including Range rate data and accelerometer data, andthe model is validated using various criteria. The results show that the modelTJGRACE01S is more accurate than EIGEN-CHAMP03S model of the same degreeand order, but is little inferior to the model EIGEN-GRACE01S. The EGM96, EIGEN-CHAMP03S, TJGRACE01S and EIGEN-GRACE01S are further evaluatedwith the global 1°×1°grids geoid height differences with respect to EIGEN-GL04Ccomputed until degree/order 60, corresponding mean error of geoid height differencesare 0.446m, 0o144m, 0.027m and 0.008m respectively. (9) The gravity field model TJGRACE02S up to degree/order 80 has been computed withdynamical algorithm from the 67-day GRACE data including Range rate data andaccelerometer data, and the model is validated using various criteria. The results showthat the model TJGRACE02S is more accurate than EIGEN-CHAMP03S model ofthe same degree and order, but is little inferior to the model GGM01S. The EGM96, EIGEN-CHAMP03S, GGM01S and TJGRACE02S are further evaluated with theglobal 2.5°×2.5°grids geoid height differences and gravity anomaly differenceswith respect to EIGEN-GL04C computed until degree/order 72, corresponding meanerror of geoid height differences are 0.524m, 0.305m, 0.021m and 0.052mrespectively, and mean error of gravity anomaly differences are 4.00mGal, 3.07mGal, 0.21 mGal and 0.50 mGal respectively.(10) The main results are summarized in the last chapter, and the outlook for futurework is also made.