Xianglin Liu

Quality assessment of onboard GPS receiver and its combination with DORIS and SLR for Haiyang 2A precise orbit determination

The GPS, DORIS, and SLR instruments are installed on Haiyang 2A (HY2A) altimetry satellite for Precise Orbit Determination (POD). Among these instruments, the codeless GPS receiver is the state-of-art Chinese indigenous onboard receiver, and it is the first one successfully used for Low Earth Orbit (LEO) satellite. Firstly, the contribution assesses the performance of the receiver through an analysis of data integrity, numbers of all tracked and valid measurements as well as multipath errors. The receiver generally shows good performance and quality despite a few flaws. For example, L2 observations are often missing in low elevations, particularly during the ascent of GPS satellites, and the multipath errors of P1 show a slightly abnormal pattern. Secondly, the PCO (Phase Center Offset) and PCV (Phase Center Variation) of the antenna of the GPS receiver are determined in this contribution. A significant leap for Z-component of PCO up to −1.2 cm has been found on 10 October 2011. Thirdly, the obtained PCO and PCV maps are used for GPS only POD solutions. The post-fit residuals of ionosphere-free phase combinations reduce almost 50%, and the radial orbit differences with respect to CNES (Centre National d’Etudes Spatiales) Precise Orbit Ephemeris (POEs) improve about 13.9%. The orbits are validated using the SLR data, and the RMS of SLR Observed minus Computed (O-C) residuals reduces from 17.5 to 15.9 mm. These improvements are with respect to the orbits determined without PCO and PCV. Fourthly, six types of solutions are determined for HY2A satellite using different combinations of GPS, DORIS, and SLR data. Statistics of SLR O-C residuals and cross-comparison of orbits obtained in the contribution and the CNES POEs indicate that the radial accuracy of these orbits is at the 1.0 cm level for HY2A orbit solutions, which is much better than the scientific requirements of this mission. It is noticed that the GPS observations dominate the achievable accuracy of POD, and the combination of multiple types of observations can reduce orbit errors caused by data gaps and maintain more stable and continuous orbits.

Assessment of the Contribution of BeiDou GEO, IGSO, and MEO Satellites to PPP in Asia-Pacific Region

In contrast to the US Global Positioning System (GPS), the Russian Global Navigation Satellite System (GLONASS) and the European Galileo, the developing Chinese BeiDou satellite navigation system (BDS) consists of not only Medium Earth Orbit (MEO), but also Geostationary Orbit (GEO) as well as Inclined Geosynchronous Orbit (IGSO) satellites. In this study, the Precise Point Positioning (PPP) and PPP with Integer Ambiguity Resolution (IAR) are obtained. The contributions of these three different types of BDS satellites to PPP in Asia–Pacific region are assessed using data from selected 20 sites over more than four weeks. By using various PPP cases with different satellite combinations, in general, the largest contribution of BDS IGSO among the three kinds of BDS satellites to the reduction of convergence time and the improvement of positioning accuracy, particularly in the east direction, is identified. These PPP cases include static BDS only solutions and static/kinematic ambiguity-float and -fixed PPP with the combination of GPS and BDS. The statistical results demonstrate that the inclusion of BDS GEO and MEO satellites can improve the observation condition and result in better PPP performance as well. When combined with GPS, the contribution of BDS to the reduction of convergence time is, however, not as significant as that of GLONASS. As far as the positioning accuracy is concerned, GLONASS improves the accuracy in vertical component more than BDS does, whereas similar improvement in horizontal component can be achieved by inclusion of BDS IGSO and MEO as GLONASS.

Regular Gravity Field Variations and Mass Transport in the Earth System from DEOS Models Based on GRACE Satellite Data

Regular mass variations in the Earth system are analyzed using a new time series of gravity field models produced at DEOS. The subjects of special attention are secular trends as well as seasonal (annual and semi-annual) variations. It is found, in particular, that (i) the largest negative trends, which are associated with shrinking ice sheets in polar areas, reach 18–20 cm in terms of water height per year; (ii) the largest positive trends, which are presumably related to the post-glacial rebound, reach 7–9 cm/year; (iii) the largest peak-to-peak seasonal variations, which are mostly observed in large river basins, reach 50–100 cm/year. Furthermore, the confidence of secular trends is computed per point in order to isolate persistent trends. The set of locations where relatively small but persistent trends are observed includes Svalbard archipelago, Pamir mountains, Congo watershed, and Enderby Land in Antarctica.

Gravity Field Modeling on the Basis of GRACE Range-Rate Combinations

A new functional model is proposed for gravity field modeling on the basis of KBR data from the GRACE satellite mission. This functional model explicitly connects a linear combination of gravitational potential gradients with a linear combination of range-rate measurements at several successive epochs. The system of observation equations is solved in the least-squares sense by means of the pre-conditioned conjugate gradient method. Noise in range-rate combinations is strongly dependent on frequency, so that a proper frequency-dependent data weighting is a must. The new approach allows a high numerical efficiency to be reached. Both simulated and real GRACE data have been considered. In particular, we found that the resulting gravity field model is rather sensitive to errors in the satellite orbits. A preliminary gravity field model we obtained from a 101 day set of GRACE data has a comparable accuracy with the GGM01S model derived by CSR.

Combined modeling of the Earth’s Gravity Field from GRACE and GOCE Satellite Observations: a Numerical Study

A numerical study has been conducted in order to estimate how a gravity field model obtained from GOCE data can be improved in the range of low degrees by addition of GRACE data. The GRACE data are simulated as inter-satellite accelerations. Different types of noise in the inter-satellite accelerations are considered, including white noise. The gravity field model is represented as a series of spherical harmonics; the Stokes coefficients are computed by a least-squares adjustment. It is shown that the incorporation of GRACE data may improve a GOCE-based gravity field model up to degree 120 or even higher depending on the type of noise in the inter-satellite accelerations. Moreover, the joint model at lower degrees may show a significantly higher quality that either a stand-alone GOCE-based or a stand-alone GRACE-based model. It is important, however, that proper covariance matrices of the involved data sets are used in the joint data processing.

Water Storage in Africa from the Optimised GRACE Monthly Models: Iterative Approach

Water storage variability in southern Africa and particularly in the Zambezi river basin is evaluated using optimally smoothed GRACE gravity field models recently developed at Delft University of Technology. Poor availability and low quality of hydrological in situ data make independent GRACE estimates valuable for hydrological modeling.The output of available hydrological models in the target areas is therefore used for the quantification of the sample correlation and the main discrepancy between the water storage estimates from GRACE and hydrology. Moreover, an attempt to identify the main sources of the discrepancy is made.The results of the study show the maximum sample correlation between optimal water storage estimates from GRACE and from the Lumped Elementary Watershed (LEW) regional hydrological model in the North and North-East of the Zambezi river basin. The maximum discrepancy of about 0.025 m between the mean water storage variations over the Zambezi river basin from LEW and GRACE has been observed in spring, when the water storage is the largest.The estimated signal leakage (bias) caused by the optimal filtering is practically negligible when compared with the GRACE estimates produced by other research centers, though it is considerable for hydrological applications and would require a bias correction for areas smaller then \(0.5 \cdot 10^6 km^2\).A large discrepancy between LEW regional hydrological models of release 2008 (LEW-R2008) and 2006 (LEW-R2006) has been unexpectedly observed, especially in fall 2004 and spring 2005. This finding is presumably related to the use of the suspected higher quality of TRMM rainfall data with respect to FEWS rainfall data, respectively.It is finally concluded that the optimal GRACE estimates can be beneficially used to constrain regional hydrological models for their further improvement.