Evaluation of the impact of atmospheric pressure loading modeling on GNSS data analysis

In recent years, several studies have demonstrated the sensitivity of Global Navigation Satellite System (GNSS) station time series to displacements caused by atmospheric pressure loading (APL). Different methods to take the APL effect into account are used in these studies: applying the corrections from a geophysical model on weekly mean estimates of station coordinates, using observation-level corrections during data analysis, or solving for regression factors between the station displacement and the local pressure. The Center for Orbit Determination in Europe (CODE) is one of the global analysis centers of the International GNSS Service (IGS). The current quality of the IGS products urgently asks to consider this effect in the regular processing scheme. However, the resulting requirements for an APL model are demanding with respect to quality, latency, and—regarding the reprocessing activities—availability over a long time interval (at least from 1994 onward). The APL model of Petrov and Boy (J Geophys Res 109:B03405, 2004) is widely used within the VLBI community and is evaluated in this study with respect to these criteria. The reprocessing effort of CODE provides the basis for validating the APL model. The data set is used to solve for scaling factors for each station to evaluate the geophysical atmospheric non-tidal loading model. A consistent long-term validation of the model over 15years, from 1994 to 2008, is thus possible. The time series of 15years allows to study seasonal variations of the scaling factors using the dense GNSS tracking network of the IGS. By interpreting the scaling factors for the stations of the IGS network, the model by (2004) is shown to meet the expectations concerning the order of magnitude of the effect at individual stations within the uncertainty given by the GNSS data processing and within the limitations due to the model itself. The repeatability of station coordinates improves by 20% when applying the effect directly on the data analysis and by 10% when applying a post-processing correction to the resulting weekly coordinates compared with a solution without taking APL into accoun

Combination of GNSS and SLR observations using satellite co-locations

Satellite Laser Ranging (SLR) observations to Global Navigation Satellite System (GNSS) satellites may be used for several purposes. On one hand, the range measurement may be used as an independent validation for satellite orbits derived solely from GNSS microwave observations. On the other hand, both observation types may be analyzed together to generate a combined orbit. The latter procedure implies that one common set of orbit parameters is estimated from GNSS and SLR data. We performed such a combined processing of GNSS and SLR using the data of the year 2008. During this period, two GPS and four GLONASS satellites could be used as satellite co-locations. We focus on the general procedure for this type of combined processing and the impact on the terrestrial reference frame (including scale and geocenter), the GNSS satellite antenna offsets (SAO) and the SLR range biases. We show that the combination using only satellite co-locations as connection between GNSS and SLR is possible and allows the estimation of SLR station coordinates at the level of 1-2cm. The SLR observations to GNSS satellites provide the scale allowing the estimation of GNSS SAO without relying on the scale of any a priori terrestrial reference frame. We show that the necessity to estimate SLR range biases does not prohibit the estimation of GNSS SAO. A good distribution of SLR observations allows a common estimation of the two parameter types. The estimated corrections for the GNSS SAO are 119mm and −13mm on average for the GPS and GLONASS satellites, respectively. The resulting SLR range biases suggest that it might be sufficient to estimate one parameter per station representing a range bias common to all GNSS satellites. The estimated biases are in the range of a few centimeters up to 5cm. Scale differences of 0.9ppb are seen between GNSS and SL

COST-G gravity field models: application in SLR orbit determination

The Combination Service for Time-varible Gravity fields (COST-G), as a product center of the International Gravity Field Service (IGFS) of the International Association of Geodesy (IAG), provides monthly GRACE, GRACE-FO and Swarm gravity fields that are combined from the contributions of the associated analysis centers and partner analysis centers worldwide. To support operational Precise Orbit Determination (POD) of Low Earth Orbiters (LEO), where the GRACE-FO monthly gravity fields cannot meet the latency requirenments, COST-G is providing a Fitted Signal Model (FSM) that allows for the prediction of temporal gravity field variations. The COST-G FSM is updated quarterly with the latest GRACE-FO data and therefore is always based on the most recent gravity fields available. We will present the COST-G FSM and its application for the daily SLR routine processing of LAGEOS/ETALON, as well as LARES orbit determination

Between-satellite ambiguity resolution based on preliminary GNSS orbit and clock information using a globally applied ambiguity clustering strategy.

The use of undifferenced (UD) processing schemes of GNSS measurements is becoming more and more popular for the generation of global network solutions (GNSS orbits and clock products) within the GNSS community. As opposed to classical processing schemes, which are based on a two-step approach where the orbits (generally, the contributions to the observation geometry) are estimated in a double-difference (DD) scheme while leaving the estimation of the corresponding clock information (and other linear terms) to a second, independent UD procedure where the orbits are introduced as known, the newer designs combine both parts into a single, compact processing scheme. Although this offers a higher flexibility, some challenges arise from the handling of the many parameters, as well as from the implementation of robust ambiguity resolution (AR) strategies. The latter could lead to a prohibitive computational time for a growing size of the network due to the large amount of ambiguity parameters. To overcome that issue, we propose a new UD-AR strategy that adapts the DD-AR approach. This is accomplished by carefully inspecting the real-valued ambiguities in a stand-alone step, where the DD-AR information is explicitly considered through the use of ambiguity clusters. As a result, the preliminary satellite orbits and clock corrections are modified to become consistent with the integer-cycle property of the carrier phase ambiguities, allowing to resolve them as integer numbers in a computationally inexpensive station-wise parallelization. This strategy is introduced and explained in detail. Moreover, it is shown that the GPS and Galileo solutions generated by this procedure are at a competitive level compared to classical DD-based solutions