The impact of the global gravity field models on the orbit determination of LAGEOS satellites

Transkrypt

1 models on the Satelitarne metody wyznaczania pozycji we współczesnej geodezji i nawigacji, Poland Krzysztof Sośnica, Daniela Thaller, Adrian Jäggi, Rolf Dach and Gerhard Beutler Astronomical Institute University of Bern, krzysztof.sosnica@aiub.unibe.ch

2 Overview models on the LAGEOS sensitivity (maximum degree and order of model), Comparison of different models, Orbit parameterization (empirical al elements), The differences between based on different models. 2

3 LAGEOS -1 and -2 LAGEOS 1 LAGEOS 2 ID number Launch date May 4, 1976 Oct 22, 1992 Sponsor United States United States and Italy RRA Diameter 60 cm 60 cm Shape sphere sphere Reflectors 426 corner cubes 426 corner cubes Weight: kg kg Inclination: Eccentricity: Semi-major axis 12,274 km 12,158 km Area to mass ratio 7.0 cm 2 /kg 7.0 cm 2 /kg Period: 225 minutes 223 minutes 3

4 Estimated parameters: LAGEOS -1 and -2 LAGEOS weekly solution Station coordinates Osculating al elements Dynamic parameters (WC/WS, S0, SC/SW) Earth rotation parameters (X-Pole, Y-Pole, LOD) Range biases (for the selected stations) ~20 stations per week 6 per week x 2 5 per week x 2 1 x 3 per day ~2 x 2 4 Bernese Software, v.5.1 ~120 parameters per week

5 Validation of models using LAGEOS 5 Year observations, Standard solution: up to degree and order 70 of model, Per week between 1932 and 3804 normal points.

6 Validation of models using LAGEOS Groundtracks of observations residuals in

7 Max. degree and order of gravity field model 7 EGM2008 up to degree and order: RMS of observation residuals [mm] Comparison of predicted and estimated s Scale [ppb] RMS radial prediction [mm] RMS along-track prediction [mm] RMS out-of-plane prediction [mm]

8 LAGEOS -1 and -2 sensitivity 8 Max. degree and order of gravity field model Number of reproduced digits without leading to zeros w.r.t. EGM2008 based on data colected over twelve months. References: Andrea Maier, Austrian Academy of Sciences

9 Validation of models using LAGEOS Gravity field model Year Max. degree Drift SLR CHAMP GRACE GOCE Ground data JGM X X EGM X X EIGEN-GL04C X X X EGM X X EIGEN51C X X X X ITG-GRACE X AIUB-CHAMP03S X AIUB-GRACE03S X GO-CONS-2-DIR-R X X GOCO02S X X X X GOCE - SST - only X X 9

10 RMS of fit for different models 10

11 RMS of fit for different models Gravity field model RMS of observation residuals [mm] Scale [ppb] Comparison of estimated and predicted s RMS radial prediction [mm] RMS along-track prediction [mm] RMS out-of-plane prediction [mm] EGM JGM ITG-GRACE2010S AIUB-CHAMP03S GOCE SST-only GOCO02S ITG-GRACE10 mod EIGEN-GL04C EIGEN51C AIUB-GRACE03S GO-CONS-2-DIR-R EGM

12 Predicted vs. estimated s Comparison between predicted and estimated s (day 138) EGM96 AIUB- GRACE03 S ITG- GRACE10 mod EIGEN51C EIGEN- GL04C GOCO02S EGM2008 GOCE SST AIUB- CHAMP03 S RMS radial prediction [mm] RMS along-track prediction [mm] RMS out-of-plane prediction [mm] The comparison between predicted and estimated s (without Helmert parameters) JGM3 GO-CONS- 2-DIR-R2 ITG- GRACE201 0

13 Low coefficients 13 Low coefficients are estimated better in the SLR-based model (EGM96, see predictions) Coefficients 9-20 are estimated better in GRACE-based models (eg. EGM2008, AIUB-GRACE03S, see RMS of the residuals) SLR GRACE LAGEOS sensitivity

14 Orbit parameterization 14 Empirical parameters

15 Orbit parameterization 15 Empirical parameters

16 Orbit parameterization GOCO02s JGM3 AIUB-CHAMP03S EGM96 EGM2008 EIGEN-GL04C GO_CONS_DIR_2I ITG-Grace03 EIGEN-51C ITG-Grace2010s AIUB-GRACE03S -3 sigma C20-3 sigma +3 sigma 16 C20 in different models

17 Orbit parameterization AIUB-GRACE03S GO_CONS_DIR_2I GOCO02s EIGEN-51C AIUB-CHAMP03S ITG-Grace2010s JGM3 EGM96 EIGEN-GL04C ITG-Grace03 EGM C20 value and drift in different models

18 Orbit parameterization RMS of the residuals without estimating WS/WC parameters 18

19 Orbit parameterization 19 Gravity field model RMS of observatio n residuals [mm] Comparison of estimated and predicted s Scale [ppb] RMS radial predictio n [mm] RMS along-track prediction [mm] RMS out-of-plane prediction [mm] EGM JGM ITG-GRACE2010S AIUB-CHAMP03S GOCE SST-only GOCO02S ITG-GRACE10 mod EIGEN-GL04C EIGEN51C AIUB-GRACE03S GO-CONS-2-DIR-R EGM RMS of the residuals without estimating WS/WC parameters

20 Orbit parameterization Lageos solution With estimation of C20 Without estimation of C20 With estimation of WS/WC Parameters highly correlated Possible Without estimation of WS/WC Possible A very good a priori value of C20 needed 20 C20 and empirical parameters

21 Orbit comparison Gravity field model EIGEN -GL04C EGM 2008 EIGEN 51C ITG- GRACE 2010S GOCE SST AIUB- CHAMP 03S AIUB- GRACE 03S ITG- GRACE 10 mod JGM EIGEN-GL04C EGM EIGEN51C ITG-GRACE2010S GOCE SST AIUB-CHAMP03S AIUB-GRACE03S 2.2 Orbit comparison (RMS of comparison of estimated s in [mm])

22 Summary The LAGEOS are sensitive up to degree 20 of underlying model, The smallest RMS of fit to the SLR data to LAGEOS-1 and LAGEOS-2 is observed for EGM2008, GO-CONS-2-DIR-R2 and AIUB-GRACE03S when estimating once-per-rev cross-track accelerations, 22 Orbits based on JGM3 differ most w.r.t. s based on other models. The similar effect is observed for ITG-GRACE2010S, when coefficients of degree one are not set to zero, The largest RMS of fit to the SLR data from LAGEOS-1 and -2 is obtained for AIUB-GRACE03S without estimating once-perrev cross-track accelerations, Some of the lowest coefficients seem to be estimated better in SLR-based models.

23 Thank you for your attention Krzysztof Sośnica, Daniela Thaller, Adrian Jäggi, Rolf Dach and Gerhard Beutler, Astronomical Institute University of Bern