Impact of covariance information of kinematic positions on orbit reconstruction and gravity field recovery

Gravity missions are equipped with onboard Global Positioning System (GPS) receivers for precise orbit determination (POD) and for the extraction of the long wavelength part of the Earth’s gravity field. As positions of low Earth orbiters (LEOs) may be determined from GPS measurements at each observation epoch by geometric means only, it is attractive to derive such kinematic positions in a first step and to use them in a second step as pseudo-observations for gravity field determination. The drawback of not directly using the original GPS measurements is, however, that kinematic positions are correlated due to the ambiguities in the GPS carrier phase observations, which in principle requires covariance information be taken into account. We use GRACE data to show that dynamic or reduced-dynamic orbit parameters are not optimally reconstructed from kinematic positions when only taking epoch-wise covariance information into account, but that essentially the same orbit quality can be achieved as when directly using the GPS measurements, if correlations in time are taken into account over sufficiently long intervals. For orbit reconstruction covariances have to be considered up to one revolution period to avoid ambiguity-induced variations of kinematic positions being erroneously interpreted as orbital variations. For gravity field recovery the advantage is, however, not very pronounced.     

Characteristics of GOCE orbits based on Satellite Laser Ranging

The Gravity field and steady-state Ocean Circulation Explorer (GOCE) was the first European Space Agency’s (ESA) Earth Explorer core mission. Through its extremely low, about 260?km above the Earth, circular, sun-synchronous orbit, the satellite gained high spatial resolution and accuracy gravity gradient, and ocean circulation data. Global Positioning System (GPS) receivers, mounted on the spacecraft, allowed the determination of reduced-dynamic and kinematic GOCE orbits, whereas Laser Retroreflector Array (LRA) dedicated to Satellite Laser Ranging (SLR) allowed an independent validation of GPS-derived orbits. In this paper, residuals between different GPS-based orbit types and SLR observations are used to investigate the sensitivity and the influence of solar, geomagnetic, and ionospheric activities on the quality of kinematic and reduced-dynamic GOCE orbits. We also analyze the quality of data provided by individual SLR sites, by detecting time biases using ascending and descending sun-synchronous GOCE orbit passes, and the residual analysis of the measurement characteristics, i.e., the dependency of SLR residuals as a function of nadir and horizontal angles. Results show a substantial vulnerability of kinematic orbit solutions to the solar F10.7 index and the ionospheric activity measured by the variations of the Total Electron Content (TEC) values. The sensitivity of kinematic orbits to the three-hour-range KP index is rather minor. The reduced-dynamic orbits are almost insensitive to indices describing ionospheric, solar, and geomagnetic activities. The investigation of individual SLR sites shows that some of them are affected by time bias errors, whereas other demonstrate systematics, such as a dependency between observation residuals and the satellite nadir angle or the horizontal azimuth angle from the SLR station to the direction of the satellite.     

GPS-only gravity field recovery with GOCE,CHAMP, and GRACE

Gravity missions such as the Gravity field and steady-state Ocean Circulation Explorer (GOCE) are equipped with onboard Global Positioning System (GPS) receivers for precise orbit determination (POD), instrument time-tagging, and the extraction of the long wavelength part of the Earth’s gravity field. The very low orbital altitude of the GOCE satellite and the availability of dense 1 s GPS tracking data are ideal characteristics to exploit the contribution of GPS high-low Satellite-to-Satellite Tracking (hl-SST) to gravity field determination. We present gravity field solutions based on about 8 months of GOCE GPS hl-SST data from 2009 and compare the results with those obtained from the CHAllenging Minisatellite Payload (CHAMP) and Gravity Recovery And Climate Experiment (GRACE) missions. The very low orbital altitude of GOCE significantly improves gravity field recovery from GPS hl-SST data above degree 20, but not for the degrees below 20, where the quality of the spherical harmonic coefficients remains essentially unchanged. Despite the limited time span of GOCE data used, the gravity field of the Earth can be resolved up to about degree 115 using GPS data only. Empirically determined phase center variations (PCVs) of the GOCE onboard GPS helix antenna are, however, mandatory to achieve this performance.     

Improved kHz-SLR tracking techniques and orbit quality analysis for LEO missions

Satellite gravity field missions such as CHAMP, GRACE and GOCE are designed as low Earth orbiting spacecraft (LEO) with orbit heights of about 250–500 km. The challenging mission objectives require a very precise knowledge of the satellite orbit position in space. For these missions precise orbit information is typically provided by GPS satellite-to-satellite tracking (SST) observations supported by satellite laser ranging (SLR).     

Gravity field models from kinematic orbits of CHAMP,GRACE and GOCE satellites

The aim of our work is to generate Earth’s gravity field models from GPS positions of low Earth orbiters. Our inversion method is based on Newton’s second law, which relates the observed acceleration of the satellite with forces acting on it. The observed acceleration is obtained as numerical second derivative of kinematic positions. Observation equations are formulated using the gradient of the spherical harmonic expansion of the geopotential. Other forces are either modelled (lunisolar perturbations, tides) or provided by onboard measurements (nongravitational perturbations). From this linear regression model the geopotential harmonic coefficients are obtained.     

Modeling and analysis of Earth’s gravity field measurement performance by inner-formation flying system

The Earth’s gravity field can be measured with high precision by constructing the purely gravitational orbit of the inner-satellite in Inner-formation Flying System (IFS), which is independently proposed by Chinese scholars and offers a new way to carry out gravity field measurement by satellite without accelerometers. In IFS, for the purpose of quickly evaluating the highest degree of recovered gravity field model and geoid error as well as analyzing the influence of system parameters on gravity field measurement, an analytical formula was established by spectral analysis method. The formula can reflect the analytical relationship between gravity field measurement performance and system parameters such as orbit altitude, the inner-satellite orbit determination error, the inner-satellite residual disturbances, data sampling interval and total measurement time. This analytical formula was then corrected by four factors introduced from numerical simulation of IFS gravity field measurement. By comparing computation results from corrected analytical formula and the actual gravity field measurement performance by CHAMP, the correctness and rationality of this analytical formula were verified. Based on this analytical formula, the influences of system parameters on IFS gravity field measurement were analyzed. It is known that gravity field measurement performance is a monotone decreasing function of orbit altitude, the inner-satellite orbit determination error, the inner-satellite residual disturbances, data sampling interval and the reciprocal of total measurement time. There is a match relationship between the inner-satellite orbit determination error and residual disturbances, in other words, the change rate of gravity field measurement performance with one of them is seriously restricted by their relative size. The analytical formula can be used to quantitatively evaluate gravity field measurement performance fast and design IFS parameters optimally. It is noted that the analytical formula and corresponding conclusions are applied to any gravity satellite which measures gravity field by satellite perturbation orbit.     

基于双频GPS观测的简化动力学最小二乘批处理精密定轨

星载双频GPS载波相位和伪距观测量已成为低轨卫星获取精确三维位置和速度信息的主要方式. 本文以非差消电离载波相位和伪距组合作为观测量,应用简化动力学最小二乘批处理方法进行地球低轨卫星的精密定轨,并给出完整定轨流程. 采用逐段常量的经验加速度对动力学模型误差进行补偿,描述了经验加速度敏感矩阵及稀疏带状矩阵求逆的有效计算方法. 利用GRACE-A卫星GPS观测数据对定轨位置精度进行分析,结果显示,三维位置定轨精度优于5cm,经验加速度在径向、切向和法向上的补偿水平不超过40nm·s^-2,大气阻力系数和辐射光压系数的估计值符合物理实际,星载接收机钟差大致呈线性并具有短周期小波动.     

Enhancing the kinematic precise orbit determination of low earth orbiters using GPS receiver clock modelling

Clock error estimation has been the focus of a great deal of research because of the extensive usage of clocks in GPS positioning applications. The receiver clock error in the spacecraft orbit determination is commonly estimated on an epoch-by-epoch basis, along with the spacecraft’s position. However, due to the high correlation between the spacecraft orbit altitude and the receiver clock parameters, estimates of the radial component are degraded in the kinematic approach. Using clocks with high stability, the predictable behaviour of the receiver oscillator can be exploited to improve the positioning accuracy, especially for the radial component. This paper introduces two GPS receiver clock models to describe the deterministic and stochastic property of the receiver clock, both of which can improve the accuracy of kinematic orbit determination for spacecraft in low earth orbit. In particular, the clock parameters are estimated as time offset and frequency offset in the two-state model. The frequency drift is also estimated as an unknown parameter in the three-state model. Additionally, residual non-deterministic random errors such as frequency white noise, frequency random walk noise and frequency random run noise are modelled. Test results indicate that the positioning accuracy could be improved significantly using one day of GRACE flight data. In particular, the error of the radial component was reduced by over 40.0% in the real-time scenario.     

Earth gravity model improvement: An alternative method for Doppler-tracked satellites

A new method of Earth gravity model improvement based on an analytical formulation of Doppler residuals is presented here in prospect of future geodetic and altimetric missions (DORIS, TOPEX/POSEIDON, ERS1). After an intermediate step of orbit improvement, disturbing forces due to gravity field mismodeling are recovered above tracking stations at satellite altitude. Some significant simulation results for SEASAT and DORIS are presented.     

On the usefulness of atmospheric and oceanic angular momentum in recovering polar motion and gravity field variations in a unified process

Earth rotation parameters (ERPs) are excited by variations in the mass distribution on the Earth’s surface and the exchange of angular momentum between the atmosphere and oceans and the solid Earth. The same mass redistribution causes temporal changes in the gravity field coefficients with the second degree harmonics related to the rotational deformation and hence to changes in the Earth’s inertial tensor. If precise models of the atmospheric and oceanic angular momentum (AM) are available solution for polar motion and degree 2 Stokes harmonics can be unified. In this study we utilize SLR tracking of LAGEOS to compare (i) degree 2 harmonics from ERPs and gravitation, and (ii) LAGEOS excitation functions and geophysical data (mass + motion). Finally, we investigate to what extent a unified approach is possible with current models for AM data and gravity mass change estimated from ERP within orbit determinations.     

Onboard orbit determination using GPS observations based on the unscented Kalman filter

Spaceborne GPS receivers are used for real-time navigation by most low Earth orbit (LEO) satellites. In general, the position and velocity accuracy of GPS navigation solutions without a dynamic filter are 25 m (1σ) and 0.5 m/s (1σ), respectively. However, GPS navigation solutions, which consist of position, velocity, and GPS receiver clock bias, have many abnormal excursions from the normal error range for space operation. These excursions lessen the accuracy of attitude control and onboard time synchronization. In this research, a new onboard orbit determination algorithm designed with the unscented Kalman filter (UKF) was developed to improve the performance. Because the UKF is able to obtain the posterior mean and covariance accurately by using the second-order Taylor series expansion through the sampled sigma points that are propagated by using the true nonlinear system, its performance can be better than that of the extended Kalman filter (EKF), which uses the linearized state transition matrix to predict the covariance. The dynamic models for orbit propagation applied perturbations due to the 40 × 40 geo-potential, the gravity of the Sun and Moon, solar radiation pressure, and atmospheric drag. The 7(8)th-order Runge–Kutta numerical integration was applied for orbit propagation. Two types of observations, navigation solutions and C/A code pseudorange, can be used at the user’s discretion. The performances of the onboard orbit determination were verified using real GPS data of the CHAMP and KOMPSAT-2 satellites. The results of the orbit determination were compared with the precision orbit ephemeris (POE) of the CHAMP and KOMPSAT-2 satellites.     

Some comparisons of orbit determination and parameter estimation based on LAGEOS 1 and LAGEOS 2 data

The modelling accuracy of the LAGEOS 1 orbit was continously improved since its launch in 1976. In spite of these experiences the modelling accuracy of LAGEOS 2 is still about 20 per cent worse. Considering e. g. only the influence of different gravity field models it has been shown that the orbital fits for arc lengths of one month is generally about 25 mm for LAGEOS 1 and more than 30 mm for LAGEOS 2. This is mainly due to the fact that LAGEOS 2 has not yet been used for the determination of most gravity field models. The influences of different model parameters on the estimation of station coordinates, Earth rotation parameters, the geogravitational coefficient, the radiation pressure coefficient, and the empirical acceleration has been studied. The differences and peculiarities of both satellites are discussed. Although the analysis of LAGEOS 2 data still does not reach the high level of LAGEOS 1 combination solutions using both satellites allow new insights, higher accuracies, and a higher time resolution for the parameters and phenomena investigated.     

Characteristics and accuracies of the GRACE inter-satellite pointing

For almost 10 years, the Gravity Recovery and Climate Experiment (GRACE) has provided information about the Earth gravity field with unprecedented accuracy. Efforts are ongoing to approach the GRACE baseline accuracy as there still remains an order of magnitude between the present error level of the gravity field solutions and the GRACE baseline. At the current level of accuracy, thorough investigation of sensor related effects is necessary as they are one of the potential contributors to the error budget. In the science mode operations, the twin satellites are kept precisely pointed with their KBR antennas towards each other. It is the task of the onboard attitude and orbit control system (AOCS) to keep the satellites in the required formation. We analyzed long time series of the inter-satellite pointing variations as they reflect the AOCS performance and characteristics. We present significant systematic effects in the inter-satellite pointing and discuss their possible sources. Prominent features are especially related to the magnetic torquer characteristics, star cameras’ performance and KBR antenna calibration parameters. The relation between the magnetic torquer attitude control and the Earth magnetic field, impact of the different performance of the two star camera heads on the attitude control and the features due to uncertainties in the calibration parameters relating the star camera frame to K-frame are discussed in detail. Proper understanding of these effects will help to reduce their impact on the science data and subsequently increase the accuracy of the gravity field solutions. Moreover, understanding the complexity of the onboard system is essential not only for increasing the accuracy of the GRACE data but also for the development of the future gravity field satellite missions.     

GOCE orbit analysis: Long-wavelength gravity field determination using the acceleration approach

The restricted sensitivity of the Gravity field and steady-state Ocean Circulation Explorer (GOCE) gradiometer instrument requires satellite gravity gradiometry to be supplemented by orbit analysis in order to resolve long-wavelength features of the geopotential. For the hitherto published releases of the GOCE time-wise (TIM) and GOCE space-wise gravity field series—two of the official ESA products—the energy conservation method has been adopted to exploit GPS-based satellite-to-satellite tracking information. On the other hand, gravity field recovery from data collected by the CHAllenging Mini-satellite Payload (CHAMP) satellite showed the energy conservation principle to be a sub-optimal choice. For this reason, we propose to estimate the low-frequency part of the gravity field by the point-wise solution of Newton’s equation of motion, also known as the acceleration approach. This approach balances the gravitational vector with satellite accelerations, and hence is characterized by (second-order) numerical differentiation of the kinematic orbit. In order to apply the method to GOCE, we present tailored processing strategies with regard to low-pass filtering, variance–covariance information handling, and robust parameter estimation. By comparison of our GIWF solutions (initials GI for “Geodätisches Institut” and IWF for “Institut für WeltraumForschung”) and the GOCE-TIM estimates with a state-of-the-art gravity field solution derived from GRACE (Gravity Recovery And Climate Experiment), we conclude that the acceleration approach is better suited for GOCE-only gravity field determination as opposed to the energy conservation method.     

GRACE gravity field modeling with an investigation on correlation between nuisance parameters and gravity field coefficients

The GRACE (Gravity Recovery And Climate Experiment) monthly gravity models have been independently produced and published by several research institutions, such as Center for Space Research (CSR), GeoForschungsZentrum (GFZ), Jet Propulsion Laboratory (JPL), Centre National d’Etudes Spatiales (CNES) and Delft Institute of Earth Observation and Space Systems (DEOS). According to their processing standards, above institutions use the traditional variational approach except that the DEOS exploits the acceleration approach. The background force models employed are rather similar. The produced gravity field models generally agree with one another in the spatial pattern. However, there are some discrepancies in the gravity signal amplitude between solutions produced by different institutions. In particular, 10%–30% signal amplitude differences in some river basins can be observed. In this paper, we implemented a variant of the traditional variational approach and computed two sets of monthly gravity field solutions using the data from January 2005 to December 2006. The input data are K-band range-rates (KBRR) and kinematic orbits of GRACE satellites. The main difference in the production of our two types of models is how to deal with nuisance parameters. This type of parameters is necessary to absorb low-frequency errors in the data, which are mainly the aliasing and instrument errors. One way is to remove the nuisance parameters before estimating the geopotential coefficients, called NPARB approach in the paper. The other way is to estimate the nuisance parameters and geopotential coefficients simultaneously, called NPESS approach. These two types of solutions mainly differ in geopotential coefficients from degree 2 to 5. This can be explained by the fact that the nuisance parameters and the gravity field coefficients are highly correlated, particularly at low degrees. We compare these solutions with the official and published ones by means of spectral analysis. It is found that our solutions are, in general, consistent with others in the spatial pattern. The water storage variations of the Amazon, Chari and Ganges river basins have also been computed. The variations computed with the NPARB approach are closer to those produced by JPL and DEOS solutions, while the variations produced with the NPESS approach are in good agreement with those produced by the CSR and GFZ solutions. A simulation study is implemented with considering realistic noise and low-frequency error. The two approaches are used to recover the true model. The NPESS solution appears closer to the true one. Therefore we are inclined to estimate the nuisance parameters simultaneously with the geopential coefficients.     

Calibration of Envisat radar altimeter over Lake Issykkul

This study presents the results of calibration/validation (C/V) of Envisat satellite radar altimeter over Lake Issykkul located in Kyrgyzstan, which was chosen as a dedicated radar altimetry C/V site in 2004. The objectives are to estimate the absolute altimeter bias of Envisat and its orbit based on cross-over analysis with TOPEX/Poseidon (T/P), Jason-1 and Jason-2 over the ocean. We have used a new method of GPS data processing in a kinematic mode, developed at the Groupe de Recherche de Geodesie Spatiale (GRGS), which allows us to calculate the position of the GPS antenna without needing a GPS reference station. The C/V is conducted using various equipments: a local GPS network, a moving GPS antenna along the satellites tracks over Lake Issykkul, In Situ level gauges and weather stations. The absolute bias obtained for Envisat from field campaigns conducted in 2009 and 2010 is between 62.1 and 63.4 ± 3.7 cm, using the Ice-1 retracking algorithm, and between 46.9 and 51.2 cm with the ocean retracking algorithm. These results differ by about 10 cm from previous studies, principally due to improvement of the C/V procedure. Apart from the new algorithm for GPS data processing and the orbit error reduction, more attention has been paid to the GPS antenna height calculation, and we have reduced the errors induced by seiche over Lake Issykkul. This has been assured using cruise data along the Envisat satellite track at the exact date of the pass of the satellite for the two campaigns. The calculation of the Envisat radar altimeter bias with respect to the GPS levelling is essential to allow the continuity of multi-mission data on the same orbit, with the expected launch of SARAL/Altika mission in 2012. Implications for hydrology in particular, will be to produce long term homogeneous and reliable time series of lake levels worldwide.     

Measuring atmospheric density using GPS–LEO tracking data

We present a method to estimate the total neutral atmospheric density from precise orbit determination of Low Earth Orbit (LEO) satellites. We derive the total atmospheric density by determining the drag force acting on the LEOs through centimeter-level reduced-dynamic precise orbit determination (POD) using onboard Global Positioning System (GPS) tracking data. The precision of the estimated drag accelerations is assessed using various metrics, including differences between estimated along-track accelerations from consecutive 30-h POD solutions which overlap by 6 h, comparison of the resulting accelerations with accelerometer measurements, and comparison against an existing atmospheric density model, DTM-2000. We apply the method to GPS tracking data from CHAMP, GRACE, SAC-C, Jason-2, TerraSAR-X and COSMIC satellites, spanning 12 years (2001–2012) and covering orbital heights from 400 km to 1300 km. Errors in the estimates, including those introduced by deficiencies in other modeled forces (such as solar radiation pressure and Earth radiation pressure), are evaluated and the signal and noise levels for each satellite are analyzed. The estimated density data from CHAMP, GRACE, SAC-C and TerraSAR-X are identified as having high signal and low noise levels. These data all have high correlations with anominal atmospheric density model and show common features in relative residuals with respect to the nominal model in related parameter space. On the contrary, the estimated density data from COSMIC and Jason-2 show errors larger than the actual signal at corresponding altitudes thus having little practical value for this study. The results demonstrate that this method is applicable to data from a variety of missions and can provide useful total neutral density measurements for atmospheric study up to altitude as high as 715 km, with precision and resolution between those derived from traditional special orbital perturbation analysis and those obtained from onboard accelerometers.     

The GLONASS-M satellite yaw-attitude model

The proper modeling of the satellites’ yaw-attitude is a prerequisite for high-precision Global Navigation Satellite System (GNSS) positioning and poses a particular challenge during periods when the satellite orbital planes are partially eclipsed. Whereas a lot of effort has been put in to examine the yaw-attitude control of GPS satellites that are in eclipsing orbits, hardly anything is known about the yaw-attitude behavior of eclipsing GLONASS-M satellites. However, systematic variations of the carrier phase observation residuals in the vicinity of the orbit’s noon and midnight points of up to ±27 cm indicate significant attitude-related modeling issues. In order to explore the GLONASS-M attitude laws during eclipse seasons, we have studied the evolution of the horizontal satellite antenna offset estimates during orbit noon and orbit midnight using a technique that we refer to as “reverse kinematic precise point positioning”. In this approach, we keep all relevant global geodetic parameters fixed and estimate the satellite clock and antenna phase center positions epoch-by-epoch using 30-second observation and clock data from a global multi-GNSS ground station network. The estimated horizontal antenna phase center offsets implicitly provide the spacecraft’s yaw-attitude. The insights gained from studying the yaw angle behavior have led to the development of the very first yaw-attitude model for eclipsing GLONASS-M satellites. The derived yaw-attitude model proves to be much better than the nominal yaw-attitude model commonly being used by today’s GLONASS-capable GNSS software packages as it reduces the observation residuals of eclipsing satellites down to the normal level of non-eclipsing satellites and thereby prevents a multitude of measurements from being incorrectly identified as outliers. It facilitates continuous satellite clock estimation during eclipse and improves in particular the results of kinematic precise point positioning of ground-based receivers.     

基于GPS的地球资源卫星精密星历外推新方法

随着技术的发展,通过星载GPS接收机直接确定卫星星历成为卫星定位的一个重要手段.GPS接收机获取的卫星星历数据是某一时刻的瞬时状态,要获取连续的卫星星历数据还需要进一步处理.常用的处理方法有几何法与动力学法.在GPS接收机给定瞬时星历频率较低的情况下,几何法的计算误差比较大,特别是只有一组瞬时星历时,无法用几何法进行轨道的外推.在分析地球资源卫星轨道特点的基础上,提出一种新的轨道缩减动力模型,该模型将卫星运动在直角坐标系中分解为简谐运动,利用模型实现了轨道外推的算法.通过试验验证,该算法可以达到较高的精度.