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GPS Solutions
Journal Prestige (SJR): 1.674
Citation Impact (citeScore): 5
Number of Followers: 28  
 
  Hybrid Journal Hybrid journal (It can contain Open Access articles)
ISSN (Print) 1521-1886 - ISSN (Online) 1080-5370
Published by Springer-Verlag Homepage  [2467 journals]
  • Cloud-based near real-time sea level monitoring using GNSS reflectometry

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      Abstract: Abstract In addition to traditional tide gauges, the ground-based global navigation satellite system reflectometry (GNSS-R) that utilizes signal-to-noise ratio data from a single GNSS receiver has become another promising alternative for sea level monitoring. However, its application is limited by retrieval precision, especially in large tidal variation environments. On the other hand, previous studies have focused on performance improvement by using post-processing strategies, which cannot support practical (near-) real-time applications. In this work, we present a method using a robust Kalman filter to provide near real-time sea level measurements based on cloud service, achieving both high precision and high temporal resolution. A coastal GNSS station BRST with large tidal variations was selected for experimental validation. First, 30 days of archived GNSS observations were used for performance assessment. It is observed that high-precision sea level retrievals with a 5-min sampling interval can be obtained, which reaches a root-mean-square error of 5.87 cm and a correlation of 99.93% compared to the tide gauge records. Then, based on the Alibaba cloud service, we implemented a near real-time sea level monitoring system by using the real-time GNSS observations streamed by the International GNSS Service real-time service. It is shown that no detectable bias is found compared with the retrievals obtained in post-processing mode, which indicates that we can remotely sense sea level variations in near real-time and further promotes ground-based GNSS-R in practical sea level monitoring applications.
      PubDate: 2023-02-05
       
  • GDDS: Python software for GNSS data download

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      Abstract: Abstract With the rapid development of global navigation satellite system (GNSS), GNSS data products have been widely used for high-precision positioning and navigation applications. They are typically downloaded from the international GNSS service (IGS) analysis centers and continuously operating reference stations (CORS). However, the conventional GNSS data download method is cumbersome, repetitive, and time-consuming, and it is challenging to meet the demands for rapid acquisition of multi-source data products. Therefore, we have developed a GNSS data download software with Python, which provides an interactive interface for the Windows or Linux operating system to realize the efficient and stable download for a large amount of GNSS data. The software includes five main function modules: Global IGS Data, Post-Processing Product, Regional CORS Data, Custom Download, and Data Decompression. It has the characteristics of diverse data products, map interaction support, and station information retrieval, which can meet the needs of different users.
      PubDate: 2023-01-30
       
  • Satellite visibility analysis considering signal attenuation by trees
           using airborne laser scanning point cloud

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      Abstract: Abstract The number of visible global navigation satellite system (GNSS) satellites is an important indicator for evaluating positioning accuracy. In urban areas, buildings and trees cause serious satellite signal obstruction and attenuation. Studies have used three-dimensional (3D) city models or 2D panoramic imagery to calculate the visibility of satellites in some areas at a certain time. However, the production of accurate 3D models involves heavy manual work and is expensive, while public panoramic imagery mainly spreads over roads and cannot support 3D analysis. Also, the existing studies seldom consider the impact of urban on satellite signals. We thus propose a method that considers the influence of both trees and buildings. A full-path propagation model for GNSS signals is established. Then, a fast visibility analysis of satellites using an airborne laser scanning point cloud is performed. Hence, the number of visible satellites at a specific time can be mapped. In addition, real-time and forecast visibility maps are generated according to the GNSS ephemeris. To verify the effectiveness of the proposed method, we collected field measurement data for qualitative and quantitative evaluation of experiments. The experiments demonstrated that the proposed method provides an easy-to-use and high-precision solution to map the spatio-temporal visibility of satellites in 3D urban space, which serves as an important reference for applications like unmanned aerial vehicles route planning.
      PubDate: 2023-01-30
       
  • Assessment of the orbital variations of GNSS GEO and IGSO satellites for
           monitoring ionospheric TEC

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      Abstract: Abstract The geostationary orbit (GEO) satellites provide a great opportunity to continuously monitor the earth system, which has shown a powerful application in ionospheric total electron content (TEC) studies. As the GEO satellites revolve the earth over the equator synchronously with the earth's rotation, the GEO satellites appear motionless in the sky. In TEC studies, the position of the GEO satellites is normally assumed to be fixed, but the actual position changes slightly. We assess the effects of the orbital variations of the GEO satellites on monitoring ionospheric TEC based on precise satellite orbit solutions or broadcast ephemeris. The results indicate that the sub-satellite points of the GEO satellites change slightly and could induce certain variations of ionospheric pierce point (IPP). The orbital inclination and the receiver location with respect to the GEO satellite mainly determine the magnitude of IPP drift. Based on simulations with an empirical ionospheric model, the TEC differences due to the fixed GEO IPP assumption are not completely negligible. The day-to-day variations of the daily GEO IPP trajectories are not stable over a long-term time scale. The daily and yearly variations of the inclined geosynchronous orbit (IGSO) are also examined. The IGSO-based TEC could be used in the day-to-day comparison for a short period, though it is not suitable for long-term TEC studies. This work provides additional clues to improve the ionospheric studies based on GEO and IGSO TECs.
      PubDate: 2023-01-27
       
  • An investigation of PPP time transfer via BDS-3 PPP-B2b service

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      Abstract: Abstract Since 2020, China's Beidou has begun to provide an initial real-time precise point positioning (PPP) service via B2b signals for the Asia–Pacific region. It is expected to be used to achieve centimeter-level positioning and also brings opportunities for real-time time transfer. We collected 29 days of experimental data and compared it with the Centre National d’Etudes Spatiales (CNES) real-time products. The quality of the satellite's orbit and clock was analyzed first. Then, time transfer based on BDS-3, GPS, and BDS-3/GPS PPP was investigated. The results showed that the GPS PPP with the PPP-B2b is not recommended. The time transfer based on BDS-3 PPP using the PPP-B2a is feasible and achieves a 0.30 ns level. Importantly, the reliability of time transfer using the PPP-B2b outperforms that of PPP using CNES products due to the problem of unstable internet communication. Furthermore, compared to BDS-3-only, the precision of time transfer based on BDS-3/GPS PPP was not improved significantly.
      PubDate: 2023-01-26
       
  • Performance of the local ionospheric model in resolving GPS baseline
           ambiguity over the Malaysian region

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      Abstract: Abstract The positioning and navigation accuracy of the Global Positioning System (GPS) is highly affected by ionospheric conditions, especially in the Malaysian region, which is located over the equator, where there are several ionospheric irregularities. Using a dense network of GPS over the Malaysian region, we derived the ionospheric parameter, total electron content (TEC), to investigate its trends during the solar cycle 24. Subsequently, the GPS-derived TEC served as a local ionospheric model to evaluate its performance in resolving the ambiguity of the GPS baselines of different lengths, together with the global ionospheric model during the day with the occurrences of ionospheric plasma bubbles. The performance of the models was analyzed in terms of the percentage improvement in ambiguity resolution, baseline vector differences, and station coordinate repeatability. Implementing the local ionospheric models improved the percentage of ambiguity resolution by at least should 40% compared to the global ionospheric model for baselines of less than 1000 km during the day with the occurrences of an equatorial plasma bubble (EPB). A comparison of the baseline vectors showed that the local ionospheric model had minimal differences compared to the global ionospheric model. The local ionospheric model provided the minimum RMS of station coordinate repeatability with a value of less than 6 mm for a baseline of less than 1000 km during the occurrences of the EPB. These results indicate that the local ionospheric model is necessary to improve and support positioning and navigation with GPS over the study area.
      PubDate: 2023-01-23
       
  • A unified cycle-slip, multipath estimation, detection and mitigation
           method for VIO-aided PPP in urban environments

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      Abstract: Abstract Accurate, continuous and reliable positioning is required in autonomous driving. The precise point positioning (PPP) technique, which can provide a global accurate positioning service using a single global navigation satellite system (GNSS) receiver, has attracted much attention. Nevertheless, due to the cycle slips and multipath effects in the GNSS signal, the performance of PPP is severely degraded in urban areas, which has a negative effect on the PPP/inertial navigation system (INS)/vision integrated navigation. Moreover, the carrier phase observations with un-modeled multipath cause false detection of small cycle slips and lead to deviation in the state variable estimation in PPP. Therefore, an effective cycle slip/multipath estimation, detection and mitigation (EDM) method is proposed. A clustering method is used to separate the cycle slips and multipath from the carrier phase observations aided by visual inertial odometry (VIO) positioning results. The influence of the carrier phase multipath on state variable estimation is reduced by adjusting the stochastic ambiguity model in the Kalman filter. The proposed EDM method is validated by vehicle experiments conducted in urban and freeway areas. Experimental results demonstrate that 0.2% cycle slip detection error is achieved by our method. Besides, the multipath estimation accuracy of EDM improves by more than 50% compared with the geometry-based (GB) method. Regarding positioning accuracy, the EDM method has a maximum of 72.2% and 63.2% improvement compared to traditional geometry-free (GF) and GB methods.
      PubDate: 2023-01-17
       
  • Random walk multipath method for Galileo real-time phase multipath
           mitigation

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      Abstract: Abstract Since the orbit repeat cycle of Galileo satellites is about 10 days, existing spatial–temporal repeatability-based station multipath mitigation methods such as the modified sidereal filtering (MSF) and the multipath hemispherical map need more than one week of data in order to model the Galileo phase multipath correction. From this perspective, these methods are improper for most applications. We proposed a random walk multipath method (RWM) to resolve this problem. Since the elevation and azimuth angles between adjacent epochs do not change too much, the low-frequency phase multipath effects at adjacent epochs are similar. Multipath correction value can be estimated by the random walk model. Because the GPS satellite repeat cycle is short, GPS observations easily mitigate the multipath effect and have common coordinate parameters with Galileo. Multipath-reduced GPS signals can be a constant for separating coordinate parameters and multipath parameters. Galileo phase observation residuals of the latest day are used to calculate the variance for the random walk model. Experiment results show that compared to the traditional MSF model, the proposed RWM method can improve the Galileo residual reduction and positioning precision nearly without the need of any historical data. As for the practical real-time GNSS monitoring application in a severe multipath environment, the result shows that the new method can significantly reduce the Galileo multipath effect and subsequently yield a precise positioning solution. Moreover, the RWM method is invulnerable to the sampling rate and observation environment.
      PubDate: 2023-01-13
       
  • A weighted mean temperature model using principal component analysis for
           Greenland

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      Abstract: Abstract The weighted mean temperature (Tm) is an important parameter to convert the tropospheric zenith wet delay (ZWD) extracted from the global navigation satellite system (GNSS) signal into precipitable water vapor (PWV). The computation of Tm requires vertical or ground meteorological parameters. However, most GNSS stations in Greenland lack in situ meteorological data, resulting in an accuracy degradation of the derived PWV. Using the most recent ERA5 reanalysis data provided by the European Centre for Medium-Range Weather Forecasts (ECMWF) from 1990 to 2018, we extract the principal components from a large amount of reanalysis data and then model Tm using a data-driven principal component analysis (PCA) method. In comparison with classic periodic modeling approaches, our PCA model uses fewer parameters and considers temperature fluctuation with height. The proposed model is validated using observations from 11 radiosonde stations in Greenland from 2015 to 2019. The model’s bias and RMSE are − 0.110 and 4.447 K, respectively. The new model is also compared to the global pressure and temperature 3 (GPT3) and GTrop traditional grid models. The bias is reduced by 0.339 and 0.422 K, respectively, and the RMSE is reduced by 0.197 and 0.045 K, respectively.
      PubDate: 2023-01-11
       
  • An investigation of a voxel-based atmospheric pressure and temperature
           model

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      Abstract: Abstract Atmospheric pressure, temperature and zenith wet delay (ZWD) are important meteorological parameters for GNSS (Global Navigation Satellite Systems) data processing and GNSS meteorology. Due to the fact that not all GNSS stations are physically equipped with meteorological sensors, empirical models are widely used for the prediction of the atmospheric pressure (which can be used for the calculation of zenith hydrostatic delay (ZHD)), temperature and ZWD. However, if the reference height significantly differs from the height of the user site, the quality of the predicted meteorological parameters may be poor due to the height difference between the user site and the reference level. To address these issues, a voxel-based atmospheric pressure and temperature model, named PVoxel, was developed to improve the accuracy in the determination of both atmospheric pressures and temperatures. Ten-year ERA5 monthly mean reanalysis data were used for the development of PVoxel, and each monthly mean atmospheric pressure and temperature at each of the four selected reference heights (0, 4, 10 and 15 km) and the ZWD with its vertical decay parameter at 0 and 4 km over all globally distributed grid points (horizontal resolution 1° × 1°), i.e., at the nodes of the 3D voxels, were determined. Then, the characteristics of the annual and semi-annual variations of these parameters in the temporal domain for each node were modeled. The PVoxel model can be used to predict atmospheric pressure, temperature and ZWD at any geographic location and time. The model was evaluated by comparing the model-predicted results for the sites of all globally distributed radiosonde stations against the corresponding radiosonde data in 2019. The results showed that the atmospheric pressure and temperature predicted by PVoxel were improved significantly compared to four advanced publicly available empirical models, i.e., UNB3m, GPT3, IGPT and GTrop, especially at high altitudes. The significant improvement in the accuracy of the new model is promising for better determination of ZHD and GNSS-based applications.
      PubDate: 2023-01-10
       
  • Characteristics of the IGS receiver clock performance from multi-GNSS PPP
           solutions

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      Abstract: Abstract Global navigation satellite system (GNSS) receivers belonging to the International GNSS Service (IGS) are equipped with different types of clocks, such as internal crystal quartz clocks, rubidium and cesium atomic clocks, as well as hydrogen masers. These clocks are characterized by different phase and frequency accuracies and stabilities, resulting in different systematic clock time series patterns. We analyze the clock offsets between different GNSS systems, provide noise characteristics of the undifferenced and differenced clock parameters, and detect systematic patterns of the clocks. The time series of the receiver clocks are dominated by the diurnal, semidiurnal, and sometimes terdiurnal signals with amplitudes up to several meters. Hydrogen masers provide the highest clock stability, and the lowest is by internal clocks. However, there are also groups of very stable internal clocks that perform similarly to low-performing hydrogen masers and rubidium clocks. The interquartile ranges for epoch-differenced clock parameters fall between 3 and 250 mm for the best hydrogen masers and the worst internal clocks, respectively.
      PubDate: 2023-01-10
       
  • Realizing rapid re-convergence in multi-GNSS real-time satellite clock
           offset estimation with dual-thread integer ambiguity resolution

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      Abstract: Abstract Real-time satellite clock offsets are key in realizing real-time precise point positioning (PPP). Typically, tens of minutes are required for re-convergence because many tropospheric and ambiguity parameters are estimated in the clock offset estimation when the interruption of observation data occasionally occurs. This contribution proposes a rapid re-convergence method for multi-global navigation satellite system (GNSS) real-time satellite clock offset estimation. In case of a few seconds of interruption, the dual-thread integer ambiguity resolution method is proposed. The float clock offset, uncalibrated phase delay, fixed and float ambiguities, clock offset with IAR, zenith wet delay (ZWD) and inter-system bias (ISB) are generated in a slow thread, in which the fixed and float ambiguities, ZWD and ISB are used in a quick thread to achieve rapid re-convergence. Observations from 60 globally distributed stations were processed using the proposed method. The experimental results show that rapid re-convergence, fast estimation and high-precision clock offsets can be achieved. The re-convergence time of clock offset estimation was 0.14, 0.15, 0.74, 0.36 and 2.48 min for the GPS, Galileo, BDS-2, BDS-3 and GLONASS, respectively. Most satellite clock offsets can realize instantaneous re-convergence. The clock offset standard deviations are 0.028, 0.024, 0.069, 0.043 and 0.125 ns, respectively. The computation times were 21.4 and 1.7 s for the slow and quick threads, respectively. Compared to the float PPP solutions, the positioning accuracy of the PPP-AR was improved by 53.9, 29.9 and 18.2% from 1.80 to 0.83 cm, 1.57 to 1.10 cm and 3.63 to 2.97 cm for the east, north and up components, respectively. In case of interruptions lasting from a few minutes to tens of minutes, the ZWD, ambiguities and ISB information before interruption are used in the clock offset estimation, and a strong constraint is imposed on the normal equation, i.e., a large value (e.g., 105) is used instead of the diagonal value of the normal equation matrix corresponding to each estimated parameter. Experimental results show that rapid re-convergence can be achieved for GPS and Galileo with an interruption of 10 min, whereas the rapid re-convergence cannot be achieved for BDS-2, BDS-3 and GLONASS because of the impact of satellite orbit accuracy, error model, and neglection of the inter-frequency bias, respectively.
      PubDate: 2023-01-09
       
  • Ionospheric disturbances of the January 15, 2022, Tonga volcanic eruption
           observed using the GNSS network in New Zealand

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      Abstract: Abstract In this study, the ionospheric response related to the January 15, 2022, Tonga volcanic eruption is investigated using total electron content extracted from the global navigation satellite system network in New Zealand. Significant covolcanic ionospheric disturbances (CVIDs) are observed after the eruption. Two wide-wavelength CVIDs first appeared with a propagation speed of 581 m/s. Then, they split into two modes at about 2400 km away from the explosion center, the fast one with a speed of 643 m/s and the slow one with a speed of 380 m/s. Following the wide-wavelength CVIDs, many narrow-wavelength CVIDs occur from about 2000 km away from the explosion center with various propagation speeds of 380 m/s, 358 m/s and 252 m/s. According to the propagation characteristics, the wide-wavelength CVIDs can be attributed to the shock waves in acoustic–gravity modes excited by the volcanic eruption; the fast narrow-wavelength CVIDs (380 m/s and 358 m/s) are caused by the Lamb waves that generate atmospheric resonance at gravity wave modes, while the slow narrow-wavelength CVIDs (252 m/s) could be due to the eruption-induced gravity waves. These new observed results can provide a deeper understanding of volcano-ionosphere coupling.
      PubDate: 2023-01-06
       
  • Mixed QZSS/GPS/Galileo RTK positioning with a trade-off between
           ionosphere-weighting and ionosphere-fixed models: an ambiguity resolution
           method for Japan

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      Abstract: Abstract In real-time kinematic (RTK) positioning, the ambiguity resolution (AR) performance is critically affected by ionospheric delays. The ionospheric delays can be represented by a function of vertical total electron content values. Most of Japan is in mid-latitude regions, over which the spatial gradient of the vertical total electron content is usually small. Under the condition and after the highest pivot satellite is chosen, if more high-elevation secondary satellites are available, then the number of double-differenced (DD) measurements with small ionospheric delays (MSIDs) (e.g., < 10 cm) can increase within medium-long baselines. The mixed-constellation DD technique can produce measurements with more high-elevation secondary satellites than the classical DD technique, and at least one Quasi-Zenith Satellite System (QZSS) satellite can be constantly observed at elevations higher than 60° over the entire Japan. Therefore, the mixed-constellation DD technique, including QZSS, can make the number of DD MSIDs as large as possible in Japan. In the presence of more DD MSIDs, the AR can perform better on the premise that the ionospheric pseudo-observations are given properly. For the mixed QZSS/GPS/Galileo RTK positioning in Japan, this study proposes a cascading AR from high to low elevations to mitigate the occurrence of the improper provision of ionospheric pseudo-observations. In the analysis, the proposed and conventional AR methods are compared. The experimental results show that the success percentage of AR can improve by 41.7% and 6.3% for baselines 100 and 200 km, respectively.
      PubDate: 2023-01-05
       
  • Effect of the 2011 Tohoku-Oki earthquake on continuous GNSS station
           motions

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      Abstract: Abstract It is an indisputable fact that the GNSS time series contain colored noise. However, we find that colored noise greatly affects parameter estimation of general linear trajectory models. For the post-seismic timescale parameters, ignoring the colored noise will increase the iteration times of the calculation parameters by 10–11 times. For parameters of coefficients, ignoring colored noise will obviously increase the deviation of parameter estimates. To overcome the above problems, we first estimate colored noise by maximum likelihood estimation. Then, the nonlinear least square algorithm with colored noise as the stochastic model is used to calculate timescale parameters. Finally, general linear trajectory models are constructed by using the calculated timescale parameters, and their optimal parameters are estimated by maximum likelihood estimation. The method is validated by lots of simulation experiments. The results show that the number of iterations is reduced by 90% compared with the traditional method; the deviation for parameters of coefficients decreased significantly. These methods are applied to the 2011 Tohoku-Oki earthquake. The results show that a nonlinear least square algorithm based on an appropriate stochastic model can provide strong constraints for timescale parameters. Among them, the timescale parameters of logarithmic terms decay exponentially with the increase in the distance from the epicenter; timescale parameters of exponential terms increase linearly northward. On the other hand, colored noise is an important factor affecting the extraction of seismic signals. For co-seismic displacement, ignoring colored noise will seriously underestimate small amplitude co-seismic signals. In the northern of Tohoku with the smallest co-seismic displacement, ignoring the colored noise will underestimate the co-seismic displacement by 20 mm. For post-seismic displacement, the float caused by ignoring colored noise is up to 500 mm, and the larger float (> 200 mm) is randomly distributed in the spatial domain. Therefore, it is necessary to consider the influence of colored noise on post-seismic deformation.
      PubDate: 2023-01-04
       
  • Regional application of generalized regression neural network in
           ionosphere spatio-temporal modeling and forecasting

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      Abstract: Abstract We propose using the generalized regression neural network (GRNN) method for spatio-temporal modeling of ionosphere total electron content (TEC). The GRNN model uses radial basis functions in the pattern layer. Therefore, the accuracy and convergence speed to the optimal solution of this model are higher compared to the other machine learning models. The efficiency of the new model has been evaluated using observations of 30 global navigation satellite system (GNSS) stations in central Europe at 2015. It should be noted that the training of the GRNN model is done using the latitude and longitude of GNSS station, day of year, hours, AP, KP and DST geomagnetic indices and solar activity index (F10.7). Also, the vertical TEC corresponding to these input parameters is desirable output. The results of the new model have been compared with the results of the artificial neural network, adaptive neuro-fuzzy inference system, support vector regression, ordinary Kriging, global ionosphere map and the international reference ionosphere 2016 (IRI2016) empirical model as well as precise point positioning (PPP) method. The obtained results show that in both high and low geomagnetic and solar activities, the GRNN model has a higher accuracy with respect to the other models. The analysis of the PPP method shows an improvement of 37 mm in the coordinate components using GRNN model. The results show that the GRNN model can be considered as an alternative to global and empirical ionosphere models. The GRNN model is a high-precision regional ionosphere model.
      PubDate: 2023-01-04
       
  • Tropospheric parameters from multi-GNSS and numerical weather models: case
           study of severe precipitation and flooding in Germany in July 2021

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      Abstract: Abstract Storms and floods are the most frequent natural disaster in western and central Europe. Due to climate change, intensive storms with prolonged rain episodes will continue to cause even more destructive flooding. The good understanding and forecasting of such events are thus of uttermost importance. One of the ways to improve weather forecasts is the assimilation of external data, such as the global navigation satellite systems (GNSS). In this study, a preparation of the multi-GNSS tropospheric products—zenith total delays, tropospheric gradients and slant total delays—for future operational assimilation is shown. For a severe precipitation event in July 2021 in Germany, the GNSS parameters from three systems—GPS, GLONASS and Galileo—are compared to three Numerical Weather Models (NWMs)—ERA5 reanalysis of ECMWF, ICON run by the German Weather Service and GFS run by the US Weather Service. The flood that followed the rainfall was the deadliest natural disaster in Germany since 1962. The results show that all considered GNSS solutions have a similar level of agreement with the NWMs. However, for the flood region in western Germany, the biases from the multi-GNSS solutions are smaller compared to the GPS-only solution. From the models, ICON has the highest agreement with the GNSS data for all considered tropospheric parameters. The best agreement with the ICON is probably due to its high horizontal resolution and, thus, low representative errors and the fine tuning of DWD’s regional model for the specific region (Germany).
      PubDate: 2023-01-03
       
  • Estimating GPS satellite and receiver differential code bias based on
           signal distortion bias calibration

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      Abstract: Abstract Differential code bias (DCB) is an important error source in Global Navigation Satellite System (GNSS) data processing. Currently, DCBs are generally divided into satellite-specific and receiver-specific parts. However, the chip shape of live signal differs from the ideal rectangle. Such signal distortion on the chip shapes will lead to systematic bias in pseudorange observations, namely signal distortion bias (SDB), which affects the accuracy of DCB estimation when different receiver types are used. Therefore, this research aims to estimate satellite and receiver DCBs based on SDB calibration and to explore how SDB affects DCB. Theoretical analysis shows receiver DCB absorbs the average SDBs and satellite DCB absorbs the rest of SDBs. Thus, the existence of SDBs results in the inconsistency of DCB estimated by different types of receivers. Abundant GNSS observations from the year 2017 to 2019 are adopted to assess DCB estimation, and the results validate that there are large biases for GPS satellite DCBs among different receiver groups if SDBs are ignored. However, the biases greatly decrease once SDBs are corrected, and the average improvement is 60.0%. The long-term variations of some satellite DCB can be attributed to the SDBs and variations of receiver group proportions in the observation network. With SDB correction, the variations in satellite DCB time series greatly decrease, especially for those intra-frequency DCB products. As for the receiver DCB, the SDB only creates a systematic bias against it and generally remains unchanged unless the satellite is changed, the receiver is replaced, or the receiver firmware is updated. Overall, the accuracy of satellite DCB improves with SDB correction in terms of consistency among different receiver groups and their long-term stabilities.
      PubDate: 2023-01-02
       
  • Characteristic differences in tropospheric delay between Nevada Geodetic
           Laboratory products and NWM ray-tracing

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      Abstract: Abstract Numerical weather models (NWMs) are important data sources for space geodetic techniques. Additionally, the Global Navigation Satellite System (GNSS) provides many observations to continuously improve and enhance the NWM. Existing comparative analysis experiments on NWM tropospheric and GNSS tropospheric delays suffer from being conducted in highly specific regions with limited spatial coverage; furthermore, the length of time for the experiment is too short for analyzing seasonal characteristics, and the insufficient number of stations limits spatial density, making it difficult to obtain the equipment-dependent distribution characteristics. After strict quality control and data preprocessing, we have calculated and compared the bias and standard deviation of tropospheric delay for approximately 7000 selected Nevada Geodetic Laboratory (NGL) GNSS stations in 2020 with the European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis v5 (ERA5) hourly ray-traced tropospheric delay for the same group of stations. Characterizations in time, space, and linkage to receivers and antennas reveal positive biases of approximately 4 mm in the NGL zenith tropospheric delay (ZTD) relative to the NWM ZTD over most of the globe; moreover, there is a seasonal amplitude reaching 6 mm in the bias, and an antenna-related mean bias of approximately 1.6 mm in the NGL tropospheric delay. The obtained results can be used to provide a priori tropospheric delays with appropriate uncertainties; additionally, they can be applied to assess the suitability of using NWMs for real-time positioning solutions.
      PubDate: 2023-01-02
       
  • Markov chain Monte Carlo-based DCPB estimation for ambiguity fixing of
           GLONASS-only FDMA single-epoch positioning

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      Abstract: Abstract The differential inter-frequency biases (DIFB) caused by the differential code phase biases (DCPB) between inhomogeneous stations are correlated with the ambiguity parameters and are difficult to estimate in GLONASS FDMA precise positioning. Without known DIFB, the double difference (DD) ambiguity cannot be fixed or only partial ambiguity resolution is achievable. The Monte Carlo-based method can estimate DIFB with sampled values where if only some samples are close enough to the true value, the unknown phase bias parameter can be estimated successfully and thus enable high precision positioning. This study implements the Markov chain Monte Carlo (MCMC) method to refine the sample distribution in DCPB estimation with GLONASS-only single-epoch observations. As a result, the procedure enables GLONASS-only FDMA ambiguity fixing and achieves single-epoch precise positioning even though the baseline and DIFB are unknown in advance. Also, the computation load of MCMC procedure is further reduced by merging the common computations of different samples in the ambiguity fixing step. The experiments with baselines OHI3_OHI2, WTZ2_WTZZ and TLSE_TLSG on 30 days show that the fix rates reach 93.6%, 89.1% and 85.0%, respectively, with baseline solution errors within [0.025, 0.025, 0.050]m. The positioning computation at each epoch takes only tens of milliseconds.
      PubDate: 2022-12-30
       
 
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