Comparison of Density Estimation for CHAMP and GRACE Satellites

Fattig, E.; McLaughlin, Craig

doi:10.2514/6.2010-7976

Cited by 6 publications

(6 citation statements)

References 14 publications

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“…Fattig et al 2010, Fattig (2011), andMcLaughlin et al (2013) presented the first extensive calibration that examined the same days for CHAMP and GRACE to see if the best parameters were consistent between CHAMP and GRACE. These studies included days from the launch of GRACE in 2004 through 2009.…”

Section: Champ and Grace Calibrationmentioning

confidence: 99%

Thermosphere Density Variability, Drag Coefficients, and Precision Satellite Orbits

McLaughlin¹,

Krishna²,

Mehta³

et al. 2013

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Section: Champ and Grace Calibrationmentioning

confidence: 99%

Thermosphere Density Variability, Drag Coefficients, and Precision Satellite Orbits

McLaughlin¹,

Krishna²,

Mehta³

et al. 2013

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“…The best set of density and ballistic coefficient correlation half‐lives was found as 180 min for the density correlation half‐life, and 1.8 min for the ballistic coefficient half‐life with CIRA 1972 as a baseline density model by comparing POE‐derived densities to accelerometer‐derived densities for the CHAMP and GRACE satellites in Lechtenberg [], Fattig et al . [], and McLaughlin et al . [].…”

Section: Methodsmentioning

confidence: 99%

Thermospheric density variations: Observability using precision satellite orbits and effects on orbit propagation

et al. 2013

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[1] This paper examines atmospheric density estimated using precision orbit ephemerides (POE) from the CHAMP and GRACE satellites during short periods of greater atmospheric density variability. The results of the calibration of CHAMP densities derived using POEs with those derived using accelerometers are examined for three different types of density perturbations, [traveling atmospheric disturbances (TADs), geomagnetic cusp phenomena, and midnight density maxima] in order to determine the temporal resolution of POE solutions. In addition, the densities are compared to High-Accuracy Satellite Drag Model (HASDM) densities to compare temporal resolution for both types of corrections. The resolution for these models of thermospheric density was found to be inadequate to sufficiently characterize the short-term density variations examined here. Also examined in this paper is the effect of differing density estimation schemes by propagating an initial orbit state forward in time and examining induced errors. The propagated POE-derived densities incurred errors of a smaller magnitude than the empirical models and errors on the same scale or better than those incurred using the HASDM model.

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“…v r and ρ are the velocity of the satellite and the atmospheric density, respectively. The Jacchia 1971 model was a widely used standard [11,17]. The Jacchia model considers all the solar phenomena and adds temperature and/or density corrections to each of the phenomena within the integration of the conduction equation.…”

Section: Atmospheric Drag Modelmentioning

confidence: 99%

“…For a certain phenomenon, this model uses the curve fitting method on a real spacecraft data to precisely signify actual atmospheric conditions. However, this method limits the model for a real-time application because it has no standard set of lookup tables, and the temperature and density profile must be determined by numerical integration every single time [17].…”

Section: Atmospheric Drag Modelmentioning

confidence: 99%

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Analysis of Precise Orbit Predictions for a HY-2A Satellite with Three Atmospheric Density Models Based on Dynamic Method

et al. 2018

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HY-2A (Haiyang 2A) is the first altimetry satellite in China, and it was designed to be in a repeated ground track orbit to achieve the mission targets. Maneuvers are necessary to keep the satellite on the designed orbit according to the dynamic precise orbital prediction. Atmospheric density models are essential for predicting the low Earth orbit (LEO) satellites, such as HY-2A. Nevertheless, it is a complex process to determine the optimal atmospheric density model for orbit prediction. In this paper, short-term and long-term orbit predictions based on the dynamic method using three different atmospheric density models are tested. Detailed comparisons and evaluation of the accuracy of the predicted results are performed. Furthermore, to assess the results for the ground tracking of the satellite, the interpolation method especially for a spherical surface is introduced. The results show that among the three models, the Jacchia 1971 model is in the closest agreement with Multi-Mission Ground Segment for Altimetry precise positioning and Orbitography (SSALTO) precise orbits. The root-mean-squares (RMSs) of radial orbit differences between the predicted and precise orbits are 0.016 m, 0.091 m, 0.176 m, 0.573 m, and 1.421 m for predicted 1-h, 12-h, 1-day, 3-day, and 7-day arcs, respectively.

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Comparison of Density Estimation for CHAMP and GRACE Satellites

Cited by 6 publications

References 14 publications

Thermosphere Density Variability, Drag Coefficients, and Precision Satellite Orbits

Thermosphere Density Variability, Drag Coefficients, and Precision Satellite Orbits

Thermospheric density variations: Observability using precision satellite orbits and effects on orbit propagation

Analysis of Precise Orbit Predictions for a HY-2A Satellite with Three Atmospheric Density Models Based on Dynamic Method

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