Search

We have investigated the drivers behind the observed spatiotemporal mass balance heterogeneity in Tien Shan and Pamir, in High Mountain Asia. To study the consistency of the different interpretations derived from the available meteorological reanalysis and remote sensing products, we used correlation analyses between climatic and static drivers with novel estimates of region-wide annual glacier mass balance time series. These analyses were performed both spatially using different spatial classifications of glaciers and temporally for each individual glacier. Our results show that the importance of the variables studied depends strongly on the dataset used and which spatial classification of glaciers is chosen. This extends to opposing results using the different products. Even supposedly similar datasets lead to different and partly contradicting assumptions on dominant drivers of mass balance variability. The apparent but false consistencies across studies using a single dataset are related, according to our results, to the chosen dataset or spatial classification rather than to the processes or involved environmental variables. Without a glaciological, meteorological, and hydrological in situ observation network providing data that allow for the direct calibration and validation of extensive datasets, our understanding of neither the changing cryosphere at the regional scale for Tien Shan and Pamir nor glacier response to climate change or the assessment of water availability for the region's growing population can improve. [ABSTRACT FROM AUTHOR]

Spectral electrical impedance tomography (sEIT) is increasingly used to characterise the structure of subsurface systems using measurements in the megahertz to kilohertz range. Additionally, hydrogeophysical and biogeophysical processes are characterised and monitored using sEIT. The method combines multiple, spatially distributed, spectroscopic measurements with tomographic inversion algorithms to obtain images of the complex electrical resistivity distribution in the subsurface at various frequencies. Spectral polarisation measurements provide additional information about the systems under investigation and can be used to reduce ambiguities that occur if only the in-phase resistivity values are analysed. However, spectral impedance measurements are very sensitive to details of the measurement setup as well as to external noise and error components. Despite promising technical progress in improving measurement quality as well as progress in the characterisation and understanding of static polarisation signatures of the subsurface, long-term (i.e. multi-month to multi-year) monitoring attempts with fixed setups are still rare. Yet, measurement targets often show inherent non-stationarity that would require monitoring for a proper system characterisation. With the aim of improving operating foundations for similar endeavours, we here report on the design and field deployment of a permanently installed monitoring system for sEIT data. The specific aim of this monitoring installation is the characterisation of crop root evolution over a full growing season, requiring multiple measurements per day over multiple months to capture relevant system dynamics. In this contribution, we discuss the general layout and design of the monitoring setup, including the data acquisition system, additional on-site equipment, required corrections to improve data quality for high frequencies, data management and remote-processing facilities used to analyse the measured data. The choice and installation of electrodes, cables and measurement configurations are discussed and quality parameters are used for the continuous assessment of system functioning and data quality. Exemplary analysis results of the first season of operation highlight the importance of continuous quality control. It is also found that proper cable elevation decreased capacitive leakage currents and in combination with the correction of inductive effects led to consistent tomographic results up to 1 kHz measurement frequency. Overall, the successful operation of an sEIT monitoring system over multiple months with multiple daily tomographic measurements was achieved. [ABSTRACT FROM AUTHOR]

A new methodology for performing long-term source apportionment (SA) using positive matrix factorization (PMF) is presented. The method is implemented within the SoFi Pro software package and uses the multilinear engine (ME-2) as a PMF solver. The technique is applied to a 1-year aerosol chemical speciation monitor (ACSM) dataset from downtown Zurich, Switzerland. The measured organic aerosol mass spectra were analyzed by PMF using a small (14 d) and rolling PMF window to account for the temporal evolution of the sources. The rotational ambiguity is explored and the uncertainties of the PMF solutions were estimated. Factor–tracer correlations for averaged seasonal results from the rolling window analysis are higher than those retrieved from conventional PMF analyses of individual seasons, highlighting the improved performance of the rolling window algorithm for long-term data. In this study four to five factors were tested for every PMF window. Factor profiles for primary organic aerosol from traffic (HOA), cooking (COA) and biomass burning (BBOA) were constrained. Secondary organic aerosol was represented by either the combination of semi-volatile and low-volatility organic aerosol (SV-OOA and LV-OOA, respectively) or by a single OOA when this separation was not robust. This scheme led to roughly 40 000 PMF runs. Full visual inspection of all these PMF runs is unrealistic and is replaced by predefined user-selected criteria, which allow factor sorting and PMF run acceptance/rejection. The selected criteria for traffic (HOA) and BBOA were the correlation with equivalent black carbon from traffic (eBC tr) and the explained variation of m/z 60, respectively. COA was assessed by the prominence of a lunchtime concentration peak within the diurnal cycle. SV-OOA and LV-OOA were evaluated based on the fractions of m/z 43 and 44 in their respective factor profiles. Seasonal pre -tests revealed a non-continuous separation of OOA into SV-OOA and LV-OOA, in particular during the warm seasons. Therefore, a differentiation between four-factor solutions (HOA, COA, BBOA and OOA) and five-factor solutions (HOA, COA, BBOA, SV-OOA and LV-OOA) was also conducted based on the criterion for SV-OOA. HOA and COA contribute between 0.4–0.7 µgm-3 (7.8 %–9.0 %) and 0.7–1.2 µgm-3 (12.2 %–15.7 %) on average throughout the year, respectively. BBOA shows a strong yearly cycle with the lowest mean concentrations in summer (0.6 µgm-3 , 12.0 %), slightly higher mean concentrations during spring and fall (1.0 and 1.5 µgm-3 , or 15.6 % and 18.6 %, respectively), and the highest mean concentrations during winter (1.9 µgm-3 , 25.0 %). In summer, OOA is separated into SV-OOA and LV-OOA, with mean concentrations of 1.4 µgm-3 (26.5 %) and 2.2 µgm-3 (40.3 %), respectively. For the remaining seasons the seasonal concentrations of SV-OOA, LV-OOA and OOA range from 0.3 to 1.1 µgm-3 (3.4 %–15.9 %), from 0.6 to 2.2 µgm-3 (7.7 %–33.7 %) and from 0.9 to 3.1 µgm-3 (13.7 %–39.9 %), respectively. The relative PMF errors modeled for this study for HOA, COA, BBOA, LV-OOA, SV-OOA and OOA are on average ±34% , ±27% , ±30% , ±11% , ±25% and ±12% , respectively. [ABSTRACT FROM AUTHOR]

Meteors and hard targets produce coherent radar echoes. If measured with an interferometric radar system, these echoes can be used to determine the position of the target through finding the direction of arrival (DOA) of the incoming echo onto the radar. Depending on the spatial configuration of radar-receiving antennas and their individual gain patterns, there may be an ambiguity problem when determining the DOA of an echo. Radars that are theoretically ambiguity-free are known to still have ambiguities that depend on the total radar signal-to-noise ratio (SNR). In this study, we investigate robust methods which are easy to implement to determine the effect of ambiguities on any hard target DOA determination by interferometric radar systems. We apply these methods specifically to simulate four different radar systems measuring meteor head and trail echoes, using the multiple signal classification (MUSIC) DOA determination algorithm. The four radar systems are the Middle And Upper Atmosphere (MU) radar in Japan, a generic Jones 2.5λ specular meteor trail radar configuration, the Middle Atmosphere Alomar Radar System (MAARSY) radar in Norway and the Program of the Antarctic Syowa Mesosphere Stratosphere Troposphere Incoherent Scatter (PANSY) radar in the Antarctic. We also examined a slightly perturbed Jones 2.5λ configuration used as a meteor trail echo receiver for the PANSY radar. All the results are derived from simulations, and their purpose is to grant understanding of the behaviour of DOA determination. General results are as follows: there may be a region of SNRs where ambiguities are relevant; Monte Carlo simulation determines this region and if it exists; the MUSIC function peak value is directly correlated with the ambiguous region; a Bayesian method is presented that may be able to analyse echoes from this region; the DOA of echoes with SNRs larger than this region are perfectly determined; the DOA of echoes with SNRs smaller than this region completely fail to be determined; the location of this region is shifted based on the total SNR versus the channel SNR in the direction of the target; and asymmetric subgroups can cause ambiguities, even for ambiguity-free radars. For a DOA located at the zenith, the end of the ambiguous region is located at 17 dB SNR for the MU radar and 3 dB SNR for the PANSY radar. The Jones radars are usually used to measure specular trail echoes far from zenith. The ambiguous region for a DOA at 75.5 ∘ elevation and 0 ∘ azimuth ends at 12 dB SNR. Using the Bayesian method, it may be possible to analyse echoes down to 4 dB SNR for the Jones configuration when given enough data points from the same target. The PANSY meteor trail echo receiver did not deviate significantly from the generic Jones configuration. The MAARSY radar could not resolve arbitrary DOAs sufficiently well enough to determine a stable region. However, if the DOA search is restricted to 70 ∘ elevation or above by assumption, stable DOA determination occurs above 15 dB SNR. [ABSTRACT FROM AUTHOR]

Ground displacements due to ocean tide loading have previously been successfully observed using Global Positioning System (GPS) data, and such estimates for the principal lunar M2 constituent have been used to infer the rheology and structure of the asthenosphere. The GPS orbital repeat period is close to that of several other major tidal constituents (K1 , K2 , S2); thus, GPS estimates of ground displacement at these frequencies are subject to GPS systematic errors. We assess the addition of GLONASS (GLObal NAvigation Satellite System) to increase the accuracy and reliability of eight major ocean tide loading constituents: four semi-diurnal (M2 , S2 , N2 , K2) and four diurnal constituents (K1 , O1 , P1 , Q1). We revisit a previous GPS study, focusing on 21 sites in the UK and western Europe, expanding it with an assessment of GLONASS and GPS+GLONASS estimates. In the region, both GPS and GLONASS data have been abundant since 2010.0. We therefore focus on the period 2010.0–2014.0, a span considered long enough to reliably estimate the major constituents. Data were processed with a kinematic precise point positioning (PPP) strategy to produce site coordinate time series for each of three different modes: GPS, GLONASS and GPS+GLONASS. The GPS solution with ambiguities resolved was used as a baseline for performance assessment of the additional modes. GPS+GLONASS shows very close agreement with ambiguity resolved GPS for lunar constituents (M2 , N2 , O1 , Q1) but with substantial differences for solar-related constituents (S2 , K2 , K1 , P1), with solutions including GLONASS being generally closer to model estimates. While no single constellation mode performs best for all constituents and components, we propose to use a combination of constellation modes to recover tidal parameters: GPS+GLONASS for most constituents, except for K2 and K1 where GLONASS (north and up) and GPS with ambiguities resolved (east) perform best. [ABSTRACT FROM AUTHOR]

A new methodology for performing long-term source apportionment (SA) using positive matrix factorization (PMF) is presented. The method is implemented within the SoFi Pro software package and uses the multilinear engine (ME-2) as a PMF solver. The technique is applied to a one-year aerosol chemical speciation monitor (ACSM) dataset from downtown Zurich, Switzerland. The measured organic aerosol mass spectra were analyzed by PMF using a small (14 days) and rolling PMF window to account for the temporal evolution of the sources. The rotational ambiguity is explored and the uncertainty of the PMF solutions were estimated. Factor/tracer correlations for averaged seasonal results from the rolling window analysis are higher than those retrieved from conventional PMF analyses of individual seasons, highlighting the improved performance of the rolling window algorithm for long-term data. In this study four to five-factors were tested for every PMF window. Factor profiles for primary organic aerosol from traffic (HOA), cooking (COA) and biomass burning (BBOA) were constrained. Secondary organic aerosol was represented by either the combination of semi-volatile and low-volatility organic aerosol (SV-OOA and LV-OOA, respectively), or by a single OOA when this separation was not robust. This scheme leads to roughly 40 000 PMF runs. Full visual inspection of all these PMF runs is unrealistic and is replaced by predefined user-selected criteria, which allow factor sorting and PMF run acceptance/rejection. The selected criteria for traffic (HOA) and biomass burning (BBOA) were the correlation with equivalent black carbon (eBCtr) and the explained variation of m/z 60, respectively. COA was assessed by the prominence of a lunchtime concentration peak within the diurnal cycle. SV-OOA and LV-OOA were evaluated based on the fraction of m/z 43 and m/z 44 in their respective factor profiles. Seasonal pre-tests revealed a non-continuous separation of OOA into SV-OOA and LV-OOA, in particular during the warm seasons. Therefore, a differentiation between four-factor solutions (HOA, COA, BBOA and OOA) and five-factor solutions (HOA, COA, BBOA, SV-OOA and LV-OOA) was also conducted based on the criterion for SV-OOA. HOA and COA contribute between 0.4-0.7 μg m-3 (7.8-9.0 %) and 0.7-1.2 μg m-3 (12.2-15.7 %) on average throughout the year, respectively. BBOA shows a strong yearly cycle with the lowest mean concentrations in summer (0.6 μg m-3, 12.0 %), slightly higher mean concentrations during spring and fall (1.0 and 1.5 μg m-3, or 15.6 and 18.6 %, respectively), and highest mean concentrations during winter (1.9 μg m-3, 25.0 %). In summer, OOA is separated into SV-OOA and LV-OOA, with mean concentrations of 1.4 μg m-3 (26.5 %) and 2.2 μg m-3 (40.3 %), respectively. For the remaining seasons the seasonal concentrations of SV-OOA, LV-OOA and OOA range from 0.3-1.1 μg m-3 (3.4-15.9 %), 0.6-2.2 μg m-3 (7.7-33.7 %) and 0.9-3.1 μg m-3 (13.7-39.9 %), respectively. The relative PMF errors modelled for this study for HOA, COA, BBOA, LV-OOA, SV-OOA and OOA are on average ±34 %, ±27 %, ±30, ±11 %, ±25 % and ±12 %, respectively. [ABSTRACT FROM AUTHOR]

Multi-frequency signals bring a variety of combinations of different frequencies, which ispotential to improve the performance of the precise point positioning (PPP) ambiguityresolution (AR). The current Galileo constellation transmitting signals on five frequenciesincluding E1, E5a, E5b, E5 and E6 frequencies. In this contribution, we investigated theGalileo triple-frequency PPP AR based on different combinations: E1/E5a/E5b, E1/E5a/E6and E1/E5/E6. Moreover, the quadruple-frequency PPP AR method was developed inorder to utilize the observations from all available signals. Data recorded from 134International GNSS Service (IGS) stations were used to validate the effectiveness ofGalileo uncalibrated phase delay (UPD) products, and 41 stations that can observe E6signals were selected to evaluate triple-frequency and quadruple-frequency PPP ARmethod. The multipath and signal noise ratio (SNR) of Galileo observations ateach frequency was analyzed firstly, which shows that E5 signals have the highestquality. The code inter-frequency clock bias (CIFCB) was taken account of in themulti-frequency processing and it has been demonstrated that CIFCB corrections cansignificantly improve the convergence of different combinations of PPP solutionsexcept for the E1/E5a/E5b combination. The UPD products were estimated based onmulti-frequency observations with different combinations. It is interesting to find that theE5a-E5b extra-wide-lane (EWL) UPDs for all Galileo satellites are very close to zero.With the precise UPD products, the triple-frequency and quadruple-frequency PPPAR can be implemented. Numerous results show that the performance in terms ofconvergence and positioning accuracy can be obviously improved by ambiguityresolution. Moreover, the triple-frequency PPP AR also present better performance thandual-frequency PPP fixed solutions, a time to first fix (TTFF) can be improvedby 13.0%, 7.7% and 20.0% for triple-frequency PPP AR based on E1/E5a/E5b,E1/E5a/E6 and E1/E5/E6 frequency, respectively. It is worth to be mentioned thattriple-frequency PPP AR based on E1/E5/E6 frequency show the best positioningperformance with the averaged TTFF of 37.05 min. Benefited by the abundantcombinations, the quadruple-frequency PPP AR presented the best positioningperformance with the shortest convergence and the highest positioning accuracy. [ABSTRACT FROM AUTHOR]

High precision fast Real-time PPP (Precise Point Positioning) applications rely on the successful carrier phase integer ambiguity resolution. On the one hand only when carrier phase ambiguities are estimated as the correct integer values, they can act as highly precise range observations, and on the other hand fast (i.e. instantaneous or near instantaneous) precise positioning is only feasible if the ambiguities are fixed. Therefore solving PPP model is generally based on three steps. First obtain the standard least squares solution by ignoring the integer nature of the ambiguity, the so-called float solution. Second, the float ambiguity solution is computed to its integer counterpart, and finally, the estimated parameters are adjusted to the integer solution. Thereby the assumption is that the float solution is unbiased. However, any mis-specification in the functional model will usually lead to biases in the least squares estimator and thus in the float solution of the ambiguities. One of these model errors could be caused by the tropospheric delay, as it is known to be a dominant error source in high accuracy GNSS applications. The effect of this kind of delay will be increased during extreme weather events because current troposphere models are not capable of considering the complex atmosphere around the receiver during situations like typhoons, storms, heavy rainfall, etc. The focus of this contribution is on the model errors caused by the tropospheric delay and its effect on the Real-time PPP ambiguity resolution. First, a real-time recursive Detection, Identification and Adaptation (DIA) procedure is applied to detect the model errors caused by the weather events and an unbiased model is therefore proposed. Then the maximum allowable biases of integer ambiguity resolution for the biased model are identified in an analytical manner since with more parameters, the strength of the unbiased model would be reduced. The underlying model strength is also a critical factor which affects the success rate of the integer ambiguity resolution except for the model biases. In this case, whether an unbiased model is used for ambiguity resolution should be depending on the size of the bias. [ABSTRACT FROM AUTHOR]

Single-receiver GPS ambiguity resolution methods are started to be deployed for precise orbitdetermination (POD) of the Copernicus Sentinel satellites. Previous analyses from othergroups showed the improvement of the orbit results of Sentinel-3A when applyingambiguity-fixing. Prerequisite for these methods are dedicated information and productsproviding the necessary information to perform the single-receiver ambiguity resolution, e.g.,the GPS wide-lane bias product together with the corresponding orbit and clock products.Currently, these necessary inputs are and will be made available from different analysiscentres of the International GNSS Service. The Copernicus Sentinel-1, -2, and -3 orbit products delivered from the Copernicus PODService to the PDGSs (payload data ground segment) of the individual missions are not yetbased on fixed carrier phase ambiguities. Effort is taken to develop and implementcorresponding interfaces and ambiguity fixing strategies. Aim is to be able to deliverambiguity-fixed Sentinel orbits in the operational environment of the Copernicus PODService in future. The impact of the ambiguity-fixed carrier phases on the resulting Copernicus Sentinelorbit products is analysed. Due to the different latencies of the orbital products it hasto be carefully investigated for which product lines dedicated bias products areavailable in time. Backup procedures for the case that the necessary information ismissing have to be developed as well. Additionally, Sentinel-1 and -2 do not provideobservations at multiples of 10 seconds. This might complicate the applicability on thosemissions. This study will give an overview of the work done at the Copernicus POD Service tofollow up recent developments in the frame of single-receiver ambiguity resolution for PODof the Copernicus Sentinel satellites. It also includes the assessment of current and potentialfuture sources of the clock and biases needed. [ABSTRACT FROM AUTHOR]

For many years GPS and GLONNAS were leading navigation systems. However, recent years two new navigational systems have appeared. These systems are the European Galileo System and the Chinese BeiDou System. The full operability of both systems is foreseen for 2020. Galileo System is quickly developing in last years and still increasing number of satellites allows to use this system for positioning. GPS and Galileo systems share some of their signals frequencies. These shared signals frequencies allows to combine observation of both systems. The goal of this study is use the Galileo System along with GPS for positioning purpose. However still low number of Galileo satellites not allow to use this system only for precise positioning, that is why combination of GPS and Galileo is used for tests.For test purpose a self-made software was created in MatLab. It consists of three modules. First is responsible for reading RINEX files, second for the DGPS or the DGNSS in case of combined GPS and Galileo observations and the third one uses The Modified Ambiguity Function Approach (MAFA) method for precise positioning purposes. MAFA is a method of processing GNSS carrier phase observations. In this method the integer nature of ambiguities is taken into account using appropriate form of mathematical model. The theoretical Foundations of Precise Positioning Using MAFA will be presented. For test purpose data from three different days for the same baseline was used. Test was divided on two parts. In the first part short static sessions were performed for GPS only and for GPS and Galileo combination. In the second part data was tested in RTK mode for GPS only and for GPS and Galileo combination. The usage of GPS and Galileo combinations allows to increase the precision of the obtained result comparing to GPS only solution. Very important thing is to remember about inter system bias (ISB) - the difference between the receiver hardware delays affecting the signals from different systems, that can affect for the results. [ABSTRACT FROM AUTHOR]

By the end of 2018, China has successfully launched 19 new generation BDS-3 satellites, including 18 Medium Earth Orbit (MEO) satellites in operation and one Geostationary Earth Orbit (GEO) satellite under in-orbit test, to complete a primary system for providing global services. In addition to the backward BDS-2 compatible B1I (1561.098 MHz) and B3I (1269.520 MHz) signals, the new-generation BDS-3 satellites are also capable of broadcasting new B1C (1575.42 MHz) and B2a (1176.45 MHz) open service navigation signals that overlap with the GPS/Galileo L1-E1 and L5-E5a signals, which brings opportunity for the tightly combined processing or inter-system double-differencing of observations from BDS-3, GPS, and Galileo. In this presentation, for the first time we assess the interoperability of BDS-3 B1C/B2a signals with GPS/Galileo L1-E1/L5-E5a signals for tightly combined real-time kinematic (RTK) positioning using real data collected in Wuhan, China. First, the characteristics of BDS-3 B1C/B2a signals and its comparison with GPS/Galileo L1-E1/L5-E5a signals is evaluated in terms of observed carrier-to-noise density ratio, pseudorange multipath and noise, and double-differenced carrier phase and code residuals. It is demonstrated that the observational quality of BDS-3 B1C/B2a signals is comparable to that of GPS/Galileo L1-E1/L5-E5a signals. Then, we investigate the size and stability of phase and code differential inter-system bias (DISB) between BDS-3/GPS/Galileo B1C-L1-E1/B2a-L5-E5a signals using zero or short baseline data collected with receivers with both identical and different types. It is verified that the BDS-3/GPS/Galileo DISBs are indeed close to zero when identical types of receivers are used at both ends of a baseline. Moreover, they are generally present and stable in the time domain for baselines with different receiver types, which can be easily calibrated and corrected in advance. Finally, performance of single-epoch tightly combined BDS-3/GPS/Galileo RTK with single-frequency and dual-frequency observations was evaluated by a formal as well as an empirical analysis, consisting of ambiguity dilution of precision (ADOP), bootstrapped success rate (BSR), the empirical ambiguity resolution success rate, and the positioning accuracy. Experimental results from static and kinematic tests demonstrate that whether the combination is BDS-3/GPS, BDS-3/Galileo or BDS-3/GPS/Galileo, the tightly combined model (TCM) can deliver much higher BSR and lower ADOP with respect to the classical loosely combined model (LCM). Meanwhile, the empirical ambiguity resolution success rate and positioning accuracy were remarkably improved as well, especially under poor observational environments where the observed satellites for each system are limited and only single-frequency observations are available. In such cases, the improvement of the empirical ambiguity resolution success rate can reach up to approximately 10%~50%. [ABSTRACT FROM AUTHOR]

Recent studies pointed out the importance of taking into account of the multipolar components of sources of infrasonic signals associated to volcanic explosive activity. This leads to a more complex approach when inverting the data and to possible ambiguities in the results.In this work we performed a systematic analysis on synthetic datasets, taking into account various elementary source models and different network configurations. We propose a non-linear approach for the constrained inversion of the data which improves the stability of the estimated source models.For each combination we computed synthetic signals and performed both unconstrained and constrained inversions. For networks configurations with 3 or more sensors we also performed the location of the source.We quantify the correctness of each result by considering the RMS on both the data and the source-time function, the difference between the synthetic and estimated source models and the difference in source localization (when possible).Our results demonstrate that the inversion of infrasonic data is highly dependent on the network configuration and the selected source model. This highlight the needing of a critical revision of standard approaches used until now to retrieve source parameters from infrasound data. [ABSTRACT FROM AUTHOR]

In this presentation we will present our Sentinel and GPS orbits generated at the European Space Operation Centre (ESOC) as part of our Copernicus activities. We will highlight the improvements that have been made in our software (NAPEOS) as well as in our satellite modelling in recent times.The main focus of this presentation will be on the integer ambiguity resolved orbits for the Sentinel missions as well as the benefits of a fully combined processing (i.e., combining Sentinel together with the GPS satellites). In NAPEOS we are able to either resolve the integer ambiguities in a network approach in which the satellites are included in an IGS like setup or we can resolve the integer ambiguities using the GFZ/CNES method. In addition, we will address the possibilities generated by the Sentinel-3A/B close tandem phase to resolve the ambiguities in a more formation-flying like approach, using the space-baseline between the satellites flying in tandem or the baseline between two antennas on the same satellites when both nominal and redundant antenna-receiver chains were on. The results and benefits of these methods will be presented and compared.We evaluate the orbit accuracy by analysing post-fit residuals, orbit overlap errors, and orbit differences between our orbits and external orbits generated by other analysis centres. [ABSTRACT FROM AUTHOR]

GNSS-based Precise Orbit Determination (POD) of Low Earth Orbiters (LEOs) has nowadays become a standard application for high-quality GNSS products as provided by the IGS, or its individual analysis centers. For many LEOs, e.g., for altimetry missions, the centimeter absolute orbit precision and accuracy achieved by carrier phase-based GNSS positioning is mandatory and could hardly be obtained by other tracking data.Fixing the carrier phase ambiguities to their integer values has been known to inherently stabilize solutions for parameters since a long time and has been confirmed in many applications. In case of LEO POD, this has been shown extensively, e.g., by double difference processing of space or space-ground baselines for relative POD, allowing for ambiguity resolution without using any dedicated GNSS products in addition. While the processing of space baselines is feasible only for constellations of LEOs in formation flight (e.g., GRACE), the processing of space-ground baselines is very costly in computational terms if all correlations shall be modeled correctly.Single-receiver or undifferenced ambiguity fixing in Precise Point Positioning processing requires the knowledge of GNSS satellite phase biases which cancel out in forming baselines. Such products have been provided by the CNES/CLS (Centre National d'Etudes Spatiales/Collecte Localisation Satellites) analysis center of the IGS since a few years. Recently, the Center for Orbit Determination in Europe (CODE) IGS analysis center has established the generation of a high-quality signal-specific phase bias product and a fully consistent ambiguity-fixed clock product within its rapid and final IGS-related processing.On the basis of these new CODE bias and clock products, we demonstrate the performance of single-receiver ambiguity resolution for the absolute POD of the GRACE, Sentinel-3, and Swarm LEOs and compare it to results obtained by double-difference processing including ambiguity fixing. The impact of ambiguity fixing on orbit quality is assessed in terms of standard POD quality measures, independent Satellite Laser Ranging (SLR) validation, and, in case of GRACE, ultra-precise inter-satellite K-band ranging validation. [ABSTRACT FROM AUTHOR]

The GRG (CNES-CLS) IGS Analysis Center GNSS products are based on a undifferentiated processing of phase measurements. Since October 2018 Galileo data follow an undifferenced ambiguity fixation procedure similar to the GPS one. The impact on the Galileo orbits and clocks products is evaluated through orbit and clock solutions overlaps, ambiguity success rate statistics and SLR residuals. The integer property of Galileo clock products is confirmed. The success rate of ambiguity fixing is becoming close to GPS scores. The very first results of PPP with ambiguity resolution using GRG Galileo products are shown. PPP solutions from various GNSS comminations are also evaluated. [ABSTRACT FROM AUTHOR]