scholarly journals Assessment of two methods for gravity field recovery from GOCE GPS-SST orbit solutions

2003 ◽  
Vol 1 ◽  
pp. 121-126 ◽  
Author(s):  
K. Arsov ◽  
R. Pail
Keyword(s):  
Gravity Field ◽  
Numerical Integration ◽  
Precise Orbit Determination ◽  
Integral Approach ◽  
Satellite Mission ◽  
Long Wavelength ◽  
Alternative Processing ◽  
Gravity Field Recovery ◽  
Least Squares Adjustment

Abstract. In the course of the GOCE satellite mission, the high-low Satellite to Satellite Tracking (SST) observations have to be processed for the determination of the long wavelength part of the Earth’s gravity field. This paper deals with the formulation of the high-low SST observation equations, as well as the methods for gravity field recovery from orbit information. For this purpose, two approaches, i.e. the numerical integration of orbit perturbations, and the evaluation of the energy equation based on the Jacobi integral, are presented and discussed. Special concern is given to the numerical properties of the corresponding normal equations. In a closed-loop simulation, which is based on a realistic orbit GOCE configuration, these methods are compared and assessed. However, here we process a simplified case assuming that non-conservative forces can be perfectly modelled. Assuming presently achievable accuracies of the Precise Orbit Determination (POD), it turns out that the numerical integration approach is still superior, but the energy integral approach may be an interesting alternative processing strategy in the near future.Key words. High-low SST – gravity field – GOCE – variational equations – least squares adjustment

V04 Level-1 data processing status for GRACE and GRACE Follow-On

2020 ◽  
Author(s):  
Tamara Bandikova ◽  
Hui Ying Wen ◽  
Meegyeong Paik ◽  
William Bertiger ◽  
Mark Miller ◽  
...  
Keyword(s):  
Data Processing ◽  
Gravity Field ◽  
Attitude Determination ◽  
Precise Orbit Determination ◽  
Sensor Data ◽  
Satellite Mission ◽  
Gravity Field Recovery ◽  
Grace Data ◽  
Level 1 ◽  
Gravity Recovery

<p>On May 22, 2020, the Gravity Recovery and Climate Experiment Follow-On (GRACE-FO), will celebrate two years of successful in-orbit operation. The primary goal of this satellite mission is to provide information about time variations of the Earth’s gravity field. This is possible due to precise orbit determination and inter-satellite ranging by determining the relative clock alignment of the USOs, precise attitude determination and accelerometry. High quality satellite observations are one of the fundamental requirements for successful gravity field recovery. NASA/Caltech Jet Propulsion Laboratory is the official Level-1 data processing and analysis center. The GRACE-FO Level-1 data are currently being processed with software version V04. This software will be used also for final reprocessing of the GRACE (2002-2017) Level-1 data. Here we present the analysis of two years of GRACE-FO sensor data as well as a preview of the reprocessed GRACE data, and discuss the measurement performance.</p>

GRACE Follow-On Gravity Field Recovery from Combined Laser Ranging Interferometer and Microwave Ranging System Measurements

2021 ◽  
Author(s):  
Saniya Behzadpour ◽  
Andreas Kvas ◽  
Torsten Mayer-Gürr
Keyword(s):  
Gravity Field ◽  
Laser Ranging ◽  
Measurement Technology ◽  
Additional Measurement ◽  
Covariance Functions ◽  
Gravity Field Recovery ◽  
Global Gravity ◽  
Least Squares Adjustment ◽  
Noise Covariance ◽  
Component Estimation

<p>Besides a K-Band Ranging System (KBR), GRACE-FO carries a Laser Ranging Interferometer (LRI) as a technology demonstration to provide measurements of inter-satellite range changes. This additional measurement technology provides supplementary observations, which allow for cross-instrument diagnostics with the KBR system and, to some extent, the separation of ranging noise from other sources such as noise in the on-board accelerometer (ACC) measurements.</p><p>The aim of this study is to incorporate the two ranging systems (LRI and KBR) observations in ITSG-Grace2018 gravity field recovery. The two observation groups are combined in an iterative least-squares adjustment with variance component estimation used to determine the unknown noise covariance functions for KBR, LRI, and ACC measurements. We further compare the gravity field solutions obtained from the combined solutions to KBR-only results and discuss the differences with a focus on the global gravity field and LRI calibration parameters.</p>

scholarly journals PPP-based Swarm kinematic orbit determination

2018 ◽  
Author(s):  
Le Ren ◽  
Steffen Schön
Keyword(s):  
Gravity Field ◽  
Orbit Determination ◽  
External Validation ◽  
Ionospheric Scintillation ◽  
Kinematic Orbit ◽  
Cycle Slips ◽  
Gravity Field Recovery ◽  
Swarm Satellites ◽  
Least Squares Adjustment ◽  
Reduced Dynamic

Abstract. ESA's Swarm mission offers excellent opportunities to study the ionosphere and to bridge the gap in gravity field recovery between GRACE and GRACE-FO. In order to contribute to these studies, at IfE Hannover, a software based on Precise Point Positioning (PPP) batch least-squares adjustment is developed for kinematic orbit determination. In this paper, the main achievements are presented. The approach for the detection and repair of cycle slips caused by ionospheric scintillation is introduced, which is based on the Melbourne-Wübbena and ionosphere-free linear combination. The results show that around 95 % cycle slips can be repaired and the majority of the cycle slips occur on L2. After the analysis and careful preprocessing of the observations, one year kinematic orbits of Swarm satellites from Sept., 2015 to Aug., 2016 are computed with the PPP approach. The kinematic orbits are validated with the reduced-dynamic orbits published by ESA in Swarm Level 2 products and the SLR measurements. The differences between our kinematic orbits and ESA reduced-dynamic orbits are at the 1.5 cm, 1.5 cm and 2.5 cm level in the along, cross and radial track, respectively. Remaining systematics are characterised by spectral analyses. The external validation with SLR measurements shows rms errors at the 4 cm level. Finally, fully populated covariance matrices of the kinematic orbits obtained from 30 s, 10 s and 1 s data rate are discussed. It is shown that for data rates larger than 10 s, the correlation should be taken into account when using POD coordinates as input for the gravity field recovery.

scholarly journals The Uganda Gravimetric Geoid Model 2014 Computed by The KTH Method

2015 ◽  
Vol 5 (1) ◽  
Author(s):  
L. E. Sjöberg ◽  
A. Gidudu ◽  
R. Ssengendo
Keyword(s):  
Gravity Field ◽  
Gravity Data ◽  
Geoid Determination ◽  
Geopotential Model ◽  
Gravimetric Geoid ◽  
Geoid Model ◽  
Satellite Mission ◽  
Terrestrial Gravity ◽  
Gravity Field Recovery ◽  
Goce Satellite

AbstractFor many developing countries such as Uganda, precise gravimetric geoid determination is hindered by the low quantity and quality of the terrestrial gravity data. With only one gravity data point per 65 km2, gravimetric geoid determination in Uganda appears an impossible task. However, recent advances in geoid modelling techniques coupled with the gravity-field anomalies from the Gravity Field and Steady-State Ocean Circulation Explorer (GOCE) satellite mission have opened new avenues for geoid determination especially for areas with sparse terrestrial gravity. The present study therefore investigates the computation of a gravimetric geoid model overUganda (UGG2014) using the Least Squares Modification of Stokes formula with additive corrections. UGG2014 was derived from sparse terrestrial gravity data from the International Gravimetric Bureau, the 3 arc second SRTM ver4.1 Digital Elevation Model from CGIAR-CSI and the GOCE-only global geopotential model GO_CONS_GCF_2_TIM_R5. To compensate for the missing gravity data in the target area, we used the surface gravity anomalies extracted from the World Gravity Map 2012. Using 10 Global Navigation Satellite System (GNSS)/levelling data points distributed over Uganda, the RMS fit of the gravimetric geoid model before and after a 4-parameter fit is 11 cm and 7 cm respectively. These results show that UGG2014 agrees considerably better with GNSS/levelling than any other recent regional/ global gravimetric geoid model. The results also emphasize the significant contribution of the GOCE satellite mission to the gravity field recovery, especially for areas with very limited terrestrial gravity data.With an RMS of 7 cm, UGG2014 is a significant step forward in the modelling of a “1-cm geoid” over Uganda despite the poor quality and quantity of the terrestrial gravity data used for its computation.

scholarly journals Gravity Field Recovery Using High-Precision, High–Low Inter-Satellite Links

2019 ◽  
Vol 11 (5) ◽  
pp. 537 ◽  
Author(s):  
Markus Hauk ◽  
Roland Pail
Keyword(s):  
Gravity Field ◽  
Radial Component ◽  
Mass Variation ◽  
The North ◽  
Alternative Processing ◽  
Gravity Field Recovery ◽  
Satellite Links ◽  
Error Behavior ◽  
The Impact ◽  
Temporal Gravity

Past temporal gravity field solutions from the Gravity Recovery and Climate Experiment (GRACE), as well as current solutions from GRACE Follow-On, suffer from temporal aliasing errors due to undersampling of the signal to be recovered (e.g., hydrology), which arise in terms of stripes caused by the north–south observation direction. In this paper, we investigate the potential of the proposed mass variation observing system by high–low inter-satellite links (MOBILE) mission. We quantify the impact of instrument errors of the main sensors (inter-satellite link and accelerometer) and high-frequency tidal and non-tidal gravity signals on achievable performance of the temporal gravity field retrieval. The multi-directional observation geometry of the MOBILE concept with a strong dominance of the radial component result in a close-to-isotropic error behavior, and the retrieved gravity field solutions show reduced temporal aliasing errors of at least 30% for non-tidal, as well as tidal, mass variation signals compared to a low–low satellite pair configuration. The quality of the MOBILE range observations enables the application of extended alternative processing methods leading to further reduction of temporal aliasing errors. The results demonstrate that such a mission can help to get an improved understanding of different components of the Earth system.

scholarly journals Revisiting the light time correction in gravimetric missions like GRACE and GRACE follow-on

2021 ◽  
Vol 95 (5) ◽  
Author(s):  
Yihao Yan ◽  
Vitali Müller ◽  
Gerhard Heinzel ◽  
Min Zhong
Keyword(s):  
Gravity Field ◽  
Center Of Mass ◽  
Precise Orbit Determination ◽  
Relativistic Effects ◽  
Gravity Field Recovery ◽  
General Relativistic ◽  
Time Correction ◽  
The Difference ◽  
Electro Magnetic ◽  
Lower Noise

AbstractThe gravity field maps of the satellite gravimetry missions Gravity Recovery and Climate Experiment (GRACE ) and GRACE Follow-On are derived by means of precise orbit determination. The key observation is the biased inter-satellite range, which is measured primarily by a K-Band Ranging system (KBR) in GRACE and GRACE Follow-On. The GRACE Follow-On satellites are additionally equipped with a Laser Ranging Interferometer (LRI), which provides measurements with lower noise compared to the KBR. The biased range of KBR and LRI needs to be converted for gravity field recovery into an instantaneous range, i.e. the biased Euclidean distance between the satellites’ center-of-mass at the same time. One contributor to the difference between measured and instantaneous range arises due to the nonzero travel time of electro-magnetic waves between the spacecraft. We revisit the calculation of the light time correction (LTC) from first principles considering general relativistic effects and state-of-the-art models of Earth’s potential field. The novel analytical expressions for the LTC of KBR and LRI can circumvent numerical limitations of the classical approach. The dependency of the LTC on geopotential models and on the parameterization is studied, and afterwards the results are compared against the LTC provided in the official datasets of GRACE and GRACE Follow-On. It is shown that the new approach has a significantly lower noise, well below the instrument noise of current instruments, especially relevant for the LRI, and even if used with kinematic orbit products. This allows calculating the LTC accurate enough even for the next generation of gravimetric missions.

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