International GNSS Service Stations Research Articles

Global Ionospheric Model Accuracy Analysis Using Shipborne Kinematic GPS Data in the Arctic Circle

The global ionospheric model built by the International Global Navigation Satellite System (GNSS) Service (IGS) using GNSS reference stations all over the world is currently the most widely used ionospheric product on a global scale. Therefore, analysis and evaluation of this ionospheric product’s accuracy and reliability are essential for the practical use of the product. In contrast to the traditional way of assessing global ionospheric models with ground-based static measurements, our study used shipborne kinematic global positioning system (GPS) measurements collected over 18 days to perform a preliminary analysis and evaluation of the accuracy of the global ionospheric models; our study took place in the Arctic Circle. The data from the International GNSS Service stations near the Arctic Circle were used to verify the ionospheric total electron contents derived from the kinematic data. The results suggested that the global ionospheric model had an approximate regional accuracy of 12 total electron content units (TECu) within the Arctic Circle and deviated from the actual ionospheric total electron content value by about 4 TECu.

Trend estimation of zenith total delays at IGS stations by using nonparametric methods

Global Navigation Satellite System (GNSS) observations play an important role in climate studies because of the advantages they provide. An analysis of the GNSS observations can be used to obtain the zenith total delay (ZTD) parameter, which represents the effect of weather conditions. In this study, the trends of the time series of IGS (International GNSS Service) Repro1 ZTD data recorded between 1995 and 2010 at 19 GNSS stations throughout Turkey and Europe reprocessed in the framework of COST Action ES1206 were investigated. The trends of the time series were estimated by using the Mann–Kendall rank correlation test in addition to Spearman’s rho test and Sen’s slope method. In addition, the Run (Swed–Eisenhart) test was performed to test for homogeneity. The aim of this study was to evaluate the advantages and disadvantages of the applications of different methods to the estimation of trends in the ZTD time series. According to the Mann–Kendall rank correlation test, the ANKR, GRAS, HERS and MAS1 stations exhibited an increasing trend. Using the Spearman rho test, increasing trends were observed at the ANKR, EBRE and MAS1 stations, while decreasing trends were observed at the BRUS and GRAS stations. Finally, negative slope values were obtained at the BRUS, GRAS, GRAZ, HERS, JOZE, PENC and WTZR stations by using the Sen slope method.

Validation and application of optimal ionospheric shell height model for single-site estimation of total electron content

Abstract. We recently proposed a method to establish an optimal ionospheric shell height model based on the international GNSS service (IGS) station data and the differential code bias (DCB) provided by the Center for Orbit Determination in Europe (CODE) during the time from 2003 to 2013. This method is very promising for DCB and accurate total electron content (TEC) estimation by comparing to the traditional fixed shell height method. However, this method is basically feasible only for IGS stations. In this study, we investigate how to apply the optimal ionospheric shell height derived from IGS station to non-IGS stations or isolated GNSS receivers. The intuitive and practical method to estimate TEC of non-IGS stations is based on optimal ionospheric shell height derived from nearby IGS stations. To validate this method, we selected two dense networks of IGS stations located in regions in the US and Europe. Two optimal ionospheric shell height models are established by two reference stations, namely GOLD and PTBB, which are located at the approximate center of two selected regions. The predicted daily optimal ionospheric shell heights by the two models are applied to other IGS stations around these two reference stations. Daily DCBs are calculated according to these two optimal shell heights and compared to respective DCBs released by CODE. The validation results of this method are as follows. (1) Optimal ionospheric shell height calculated by IGS stations can be applied to its nearby non-IGS stations or isolated GNSS receivers for accurate TEC estimation. (2) As the distance away from the reference IGS station becomes larger, the DCB estimation error becomes larger. The relation between the DCB estimation error and the distance is generally linear.

Application of GNSS derived precipitable water vapour prediction in West Africa

Abstract Atmospheric water vapour, a major component in weather systems serves as the main source for precipitation, provides latent heat which helps maintain the earth’s energy balance and a major parameter in Numerical Weather Prediction (NWP) models. An observational technique based on the Global Navigation Satellite System (GNSS) has made it possible to easily retrieve Precipitable Water (PW) at station’s antenna position with very high spatial and temporal variabilities. GNSS techniques are superior to ground-based and balloons sensors in terms of accuracy, ease of use, wider coverage and easier assimilation into NWP models. This study sought to use prediction models using daily observational data from Four (4) International GNSS Service stations in West Africa. The best prediction model can be used in cases of station outages and to predict PW over data poor regions using computed Zenith Tropospheric Delays (ZTD). gLAB software was used to process the stations’ data in Precise Point Positioning mode and PW were retrieved using station’s temperature and pressure values. Computed PW were compared against Total Column Water Vapour from ERA-Interim Reanalysis data in 2016. Correlation coefficient (R2) values ranging from 0.947 — 0.995 were obtained for the four stations. With computed PW’s, three regression models were tested to find the best-fit with PW as the dependent variable and ZTD being the independent variable. The quadratic model gave the highest R2 and lowest RMSE values as against the linear and exponential models. Time series forecasts models such as moving average, autoregressive, exponential smoothing and autoregressive integrated moving average were also employed. The forecasts results were compared against ZTD with autoregressive model reporting the highest R2 and lowest RMSE amongst the forecast models developed.

Real-Time GPS/Galileo Precise Point Positioning Using NAVCAST Real-Time Corrections

Real-time precise point positioning (PPP) is possible through the use of real-time precise satellite orbit and clock corrections, which are available through a number of organizations including the International GNSS Service (IGS) real-time service (IGS-RTS). Unfortunately, IGS-RTS is only available for the GPS and GLONASS constellations. In 2018, a new real-time service, NAVCAST, which provides real-time precise orbit and clock corrections for the GPS and Galileo constellations, was launched. In this research, the potential performance of real-time PPP which makes use of NAVCAST real-time corrections is analyzed using various static and kinematic datasets. In the static dataset, 24 hours of observations from eight IGS stations in Canada over three different days were utilized. The static results show that the contribution of Galileo satellites can improve the positioning accuracy, with 30%, 34%, and 31% in east, north, and up directions compared to the GPS-only counterparts. In addition, centimeter-level positioning accuracy in the horizontal direction and decimeter-level positioning accuracy in the vertical direction can be achieved by adding Galileo observations. In the kinematic dataset, a real vehicular test was conducted in urban and suburban combined areas. The real-time kinematic GPS/Galileo PPP solutions demonstrate an improvement of about 53%, 45%, and 70% in east, north, and up directions compared to the GPS-only counterparts. It is shown that the real-time GPS/Galileo PPP can achieve a sub-decimeter horizontal positioning accuracy and about meter-level vertical positioning accuracy through the use of NAVCAST real-time corrections.

Enhancing real-time precise point positioning time and frequency transfer with receiver clock modeling

Thanks to the international GNSS service (IGS), which has provided an open-access real-time service (RTS) since 2013, real-time precise point positioning (RT-PPP) has become a major topic in the time community. Currently, a few scholars have studied RT-PPP time transfer, and the correlation of the receiver clock offsets between adjacent epochs have not been considered. We present a receiver clock offset model that considers the correlation of the receiver clock offsets between adjacent epochs using an a priori value. The clock offset is estimated using a between-epoch constraint model rather than a white noise model. This approach is based on two steps. First, the a priori noise variance is based on the Allan variance of the receiver clock offset derived from GPS PPP solutions with IGS final products. Second, by applying the between-epoch constraint model, the RT-PPP time transfer is achieved. Our numerical analyses clarify how the approach performs for RT-PPP time and frequency transfer. Based on five commonly used RTS products and six IGS stations, two conclusions are obtained straightforwardly. First, all RT-PPP solutions with different real-time products are capable of time transfer. The standard deviation (STD) values of the clock difference between the PPP solutions with respect to the IGS final clock products are less than 0.3 ns. Second, the STD values are reduced significantly by applying our approach. The reduction percent of STD values ranges from 4.0 to 35.5%. Moreover, the largest improvement ratio of frequency stability is 12 as compared to the solution of the white noise model. Note that the receiver clock offset from IGS final clock products is regarded as a reference.

Anomaly analysis of 18 years of newly merged GPS ephemeris from four IGS data centers

The merged GPS navigation files from the International GNSS Service (IGS) data centers, i.e., the Crustal Dynamics Data Information System (CDDIS), the Bundesamt fur Kartographie und Geodasie (BKG), the Scripps Institution of Oceanography (SIO), and the Institut Geographique National (IGN) are occasionally contaminated by anomalies and inconsistent user range accuracy (URA). This contamination impairs the performance assessment of GPS service, especially the system integrity. We remerged these files starting Day of Year (DOY) 1, 2000 using all available navigation data files from IGS stations. To effectively get the upper bound URA, a frequency-dependent pattern recognition method was developed. In addition, a comprehensive comparison between the navigation data remerged by us and those provided by the four IGS data centers was performed. The compared results revealed that TGD and Issue of Data Clock (IODC) were the dominating anomalies in the merged navigation data from CDDIS and SIO for the first several years after 2000, and M0, Ω0, ω, and af0 were the dominant anomalies in the merged data from IGN. In addition to a number of missing records, many records with incorrect PRN (pseudo-random noise number), identifying a GPS satellite, were found in files from the IGS data centers. Although the number of anomalies in the merged files from CDDIS has continued to decrease in recent years, they have not disappeared and would affect system-level assessment and scientific applications to a certain extent. The results also revealed that our remerged files were more complete, clean, compact and consistent, making them more suitable for GPS system performance assessment and related research studies. Moreover, those data are now openly available.

An Optimum Strategy for Producing Precise GPS Satellite Orbits using Double-Differenced Observations

Both the double-differenced and zero-differenced GNSS positioning strategies have been widely used by the geodesists for different geodetic applications which are demanded for reliable and precise positions. A closer inspection of the requirements of these two GNSS positioning techniques, the zero-differenced positioning, which is known as Precise Point Positioning (PPP), has gained a special importance due to three main reasons. Firstly, the effective applications of PPP for geodetic purposes and precise applications depend entirely on the availability of the precise satellite products which consist of precise satellite orbital elements, precise satellite clock corrections, and Earth orientation parameters. Secondly, the PPP processing strategy has been employed by the International GNSS Service (IGS) and IGS analysis centers to evaluate their products in terms of homogeneity and precision over a long period of time. Thirdly, the precise positions, which are determined using PPP technique, and are referenced directly to the geodetic reference frame of the satellite orbital parameters. Thus, the definition of the geodetic datum of the site coordinates using different strategies plays an enormous role in the process of generation satellite orbital parameters which have to be compatible with the corresponding satellite clock corrections and the Earth orientation parameters. This study focuses on producing uninterrupted series of satellite orbit and clock products using different criteria and assesses these products using PPP. The double-difference processing technique was used to achieve the goal of this study by Bernese GPS software version 5.0. Twenty-two globally distributed IGS stations were selected to run PPP based on the generated products and then compare the results with corresponding PPP results which were created based on the IGS rapid products. The comparison pointed to a significant improvement in the generated precise products which have considerably increased the precision of positions. What is more, this study stated that there is an observable agreement between the horizontal positions accuracies which are generated using different techniques for modeling the reference frame.

GNSS Code Multipath Short-time Fourier Transform Analysis

Global Navigation Satellite System pseudorange multipath errors cannot be analyzed with the Fourier transform as they are non-stationary; thus, other tools must be used. The objective of this paper is to investigate short-time Fourier transform (STFT) performance in detecting Global Positioning System code multipath and analyzing its frequency content. Multipath estimation was achieved by using the code-minuscarrier and the pseudorange multipath observable. Two real datasets were analyzed. A first experiment was carried out using data provided by the Jiufeng (China) International GNSS Service station. The theoretical multipath time-frequency signature was identified by analyzing time series provided by a simulator under the same conditions of the analyzed station. The spectrograms calculated on the real data and those calculated on the simulated data show the same pattern, assessing the effectiveness of the STFT performance. Based on these results, the STFT analysis was applied to a second dataset collected in a strong multipath scenario in Naples (Italy), allowing identification of the multipath sources.

A sequential network approach for estimating GPS satellite phase biases at the PPP-AR producer-side

Ambiguity resolution (AR) in precise point positioning (PPP) requires precise satellite orbit, clocks, and phase biases corrections. Satellite phase biases are fractional hardware corrections which help to retrieve the un-differenced integer carrier phase ambiguities. Satellite corrections can be obtained from the international GNSS service (IGS) or estimated by correction providers called producer-side. We introduce a new PPP-AR observation model and a new sequential network algorithm (SNA) to estimate satellite phase biases. The new model is fully compatible with standard IGS satellite correction products, and it takes advantage of currently available IGS global ionosphere maps to improve the stability of corrections estimation. Furthermore, the proposed model is full-rank per-frequency and per-site and this method simplifies the integration of any additional frequency or site observables in the system of equations. The per-site satellite phase biases method allows users to customize their network solution. In many cases, users only have to estimate the phase biases of a few satellites estimated by few stations to resolve ambiguities of their observed satellites. The novel two-step algorithm provides a good balance between the computational burden, the computer memory load, the efficiency of handling parameters, and the precise estimation of correction parameters. The proposed PPP-AR model and the SNA performance is then validated by estimating satellite phase biases with 1 year of GPS data from a sub-network of IGS stations. A rigorous a posteriori statistical test is performed using data from an independent GPS network. As a result, the precision of WL and L1 ambiguities was improved significantly with the confidence level of P > 99.99% by applying the estimated phase bias corrections to phase observables.

On the optimal height of ionospheric shell for single-site TEC estimation

The ionospheric shell height has an impact on the estimated differential code bias (DCB) and total electron content (TEC) obtained by global navigation satellite system (GNSS) data, especially for a single site. However, the shell height is generally considered as a fixed value. Based on data from the international GNSS service (IGS), we propose the concept of optimal ionospheric shell height, which minimizes |ΔDCB| when compared to the DCB provided by Center for Orbit Determination in Europe (CODE). Based on the data from five IGS stations at high, middle, and low latitudes during the time 2003–2013, we investigate the variation in the optimal ionospheric shell height and its relation with the solar activity. Results indicate that the relation between the mean of the optimal ionospheric shell height and the latitude is N-shaped. At the three stations at midlatitude, the mean value almost increases linearly with the latitude. The optimal ionospheric shell heights show 11-year and 1-year periods. The influences of the solar activity are related to the means of the optimal ionospheric shell height during the time 2003–2013. The slope of the linear fitting decreases with the mean value. Using the data from 2003 to 2013, we estimate the daily optimal ionospheric shell heights for 2014 by using the Fourier fitting method and then calculate the daily average of ΔDCB of the observed satellites by comparing to CODE results. The statistical results of the daily average in 2014 show that the optimal ionospheric shell height is much better than the fixed one. From the high-latitude station to the low-latitude station, the improvements in the mean value are about 75, 92, 96, 50, and 88% and the root-mean-squares are reduced by about 0.16, 2.09, 2.01, 1.01, and 0.02 TECu, respectively.

Estimation and analysis of multi-GNSS differential code biases using a hardware signal simulator

In ionospheric modeling, the differential code biases (DCBs) are a non-negligible error source, which are routinely estimated by the different analysis centers of the International GNSS Service (IGS) as a by-product of their global ionospheric analysis. These are, however, estimated only for the IGS station receivers and for all the satellites of the different GNSS constellations. A technique is proposed for estimating the receiver and satellites DCBs in a global or regional network by first estimating the DCB of one receiver set as reference. This receiver DCB is then used as a ‘known’ parameter to constrain the global ionospheric solution, where the receiver and satellite DCBs are estimated for the entire network. This is in contrast to the constraint used by the IGS, which assumes that the involved satellites DCBs have a zero mean. The ‘known’ receiver DCB is obtained by simulating signals that are free of the ionospheric, tropospheric and other group delays using a hardware signal simulator. When applying the proposed technique for Global Positioning System legacy signals, mean offsets in the order of 3 ns for satellites and receivers were found to exist between the estimated DCBs and the IGS published DCBs. It was shown that these estimated DCBs are fairly stable in time, especially for the legacy signals. When the proposed technique is applied for the DCBs estimation using the newer Galileo signals, an agreement at the level of 1–2 ns was found between the estimated DCBs and the manufacturer’s measured DCBs, as published by the European Space Agency, for the three still operational Galileo in-orbit validation satellites.

Global navigation satellite system detection of preseismic ionospheric total electron content anomalies for strong magnitude (Mw>6) Himalayan earthquakes

Electron content in the ionosphere is very sensitive to temporary disturbances of the Earth’s magnetosphere (geomagnetic storm), solar flares, and seismic activities. The Global Navigation Satellite System (GNSS)-based total electron content (TEC) measurement has emerged as an important technique for computations of earthquake precursor signals. We examined the pre-earthquake signatures for eight strong magnitude (Mw>6: 6.1 to 7.8) earthquakes with the aid of GNSS-based TEC measurement in the tectonically active Himalayan region using International GNSS Service (IGS) stations as well as local GNSS-based continuously operating reference stations (CORS). The results indicate very significant ionospheric anomalies in the vertical total electron content (vTEC) a few days before the main shock for all of the events. Geomagnetic activities were also studied during the TEC observation window to ascertain their role in ionospheric perturbations. It was also inferred that TEC variation due to low magnitude events could also be monitored if the epicenter lies closer to the GNSS or IGS station. Therefore, the study has confirmed TEC anomalies before major Himalayan earthquakes, thereby making it imperative to set up a much denser network of IGS/CORS for real-time data analysis and forewarning.

Simultaneous estimation of GLONASS pseudorange inter-frequency biases in precise point positioning using undifferenced and uncombined observations

GLONASS precise point positioning (PPP) performance is affected by the inter-frequency biases (IFBs) due to the application of frequency division multiple access technique. In this contribution, the impact of GLONASS pseudorange IFBs on convergence performance and positioning accuracy of GLONASS-only and GPS + GLONASS PPP based on undifferenced and uncombined observation models is investigated. Through a re-parameterization process, the following four pseudorange IFB handling schemes were proposed: neglecting IFBs, modeling IFBs as a linear or quadratic polynomial function of frequency number, and estimating IFBs for each GLONASS satellite. One week of GNSS observation data from 132 International GNSS Service stations was selected to investigate the contribution of simultaneous estimation of GLONASS pseudorange IFBs on GLONASS-only and combined GPS + GLONASS PPP in both static and kinematic modes. The results show that considering IFBs can speed up the convergence of PPP using GLONASS observations by more than 20%. Apart from GLONASS-only kinematic PPP, the positioning accuracy of GLONASS-only and GPS + GLONASS PPP is comparable among the four schemes. Overall, the scheme of estimating IFBs for each GLONASS satellite outperforms the other schemes in both convergence time reduction and positioning accuracy improvement, which indicates that the GLONASS IFBs may not strictly obey a linear or quadratic function relationship with the frequency number.

Establishment of a Site-Specific Tropospheric Model Based on Ground Meteorological Parameters over the China Region.

China is a country of vast territory with complicated geographical environment and climate conditions. With the rapid progress of the Chinese BeiDou satellite navigation system (BDS); more accurate tropospheric models must be applied to improve the accuracy of navigation and positioning. Based on the formula of the Saastamoinen and Callahan models; this study develops two single-site tropospheric models (named SAAS_S and CH_S models) for the Chinese region using radiosonde data from 2005 to 2012. We assess the two single-site tropospheric models with radiosonde data for 2013 and zenith tropospheric delay (ZTD) data from four International GNSS Service (IGS) stations and compare them to the results of the Saastamoinen and Callahan models. The experimental results show that: the mean accuracy of the SAAS_S model (bias: 0.19 cm; RMS: 3.19 cm) at all radiosonde stations is superior to those of the Saastamoinen (bias: 0.62 cm; RMS: 3.62 cm) and CH_S (bias: −0.05 cm; RMS: 3.38 cm) models. In most Chinese regions; the RMS values of the SAAS_S and CH_S models are about 0.51~2.12 cm smaller than those of their corresponding source models. The SAAS_S model exhibits a clear improvement in the accuracy over the Saastamoinen model in low latitude regions. When the SAAS_S model is replaced by the SAAS model in the positioning of GNSS; the mean accuracy of vertical direction in the China region can be improved by 1.12~1.55 cm and the accuracy of vertical direction in low latitude areas can be improved by 1.33~7.63 cm. The residuals of the SAAS_S model are closer to a normal distribution compared to those of the Saastamoinen model. Single-site tropospheric models based on the short period of the most recent data (for example 2 years) can also achieve a satisfactory accuracy. The average performance of the SAAS_S model (bias: 0.83 cm; RMS: 3.24 cm) at four IGS stations is superior to that of the Saastamoinen (bias: −0.86 cm; RMS: 3.59 cm) and CH_S (bias: 0.45 cm; RMS: 3.38 cm) models.

Precise Point Positioning Model Using Triple GNSS Constellations: GPS, Galileo and BeiDou

AbstractThis paper introduces a comparison between dual-frequency precise point positioning (PPP) post-processing model, which combines the observations of three different GNSS constellations, namely GPS, Galileo, and BeiDou and real-time PPP model. A drawback of a single GNSS system such as GPS, however, is the availability of sufficient number of visible satellites in urban areas. Combining GNSS observations offers more visible satellites to users, which in turn is expected to enhance the satellite geometry and the overall positioning solution. However, combining several GNSS observables introduces additional biases, which require rigorous modelling, including the GNSS time offsets and hardware delays. In this paper, a GNSS post-processing PPPP model is developed using ionosphere-free linear combination. The additional biases of the GPS, Galileo, and BeiDou combination are accounted for through the introduction of a new unknown parameter, which is identified as the inter-system bias, in the PPP mathematical model. Natural Resources Canada’s GPSPace PPP software is modified to enable a combined GPS / Galileo / BeiDou PPP solution and to handle the newly inter-system bias. A total of four data sets at four IGS stations are processed to verify the developed PPP model. Precise satellite orbit and clock products from the IGS-MGEX network are used to correct of the GPS, Galileo and BeiDou measurements. For the real-time PPP model the corrections of the satellites orbit and clock are obtained through the international GNSS service (IGS) real-time service (RTS). GPS and Galileo Observations are used for the GNSS RTS-IGS PPP model as the RTS-IGS satellite products are not available for BeiDou satellites. This paper provides the GNSS RTS-IGS PPP model using different satellite clock corrections namely: IGS01, IGC01, IGS01, and IGS03. All PPP models results of convergence time and positioning precision are compared to the traditional GPS-only PPP model. It is shown that combining GPS, Galileo, and BeiDou observations in a PPP model reduces the convergence time by 25 % compared with the GPS-only PPP model.

On the significance of periodic signals in noise analysis of GPS station coordinates time series

Each of the GPS-derived time series consists of the deterministic (functional) and stochastic part. We propose that the deterministic part includes all periodicities from 1st to 9th harmonics of residual Chandler, tropical and draconitic periods and compare it with commonly used calculations of the annual and semi-annual tropical curve. Then, we address the issues of whether all residual periodicities, as proposed here, need to be taken into consideration when performing noise analysis. We use the position time series from 180 International GNSS Service stations obtained at the Jet Propulsion Laboratory using the GIPSY-OASIS software in a Precise Point Positioning mode. The longest series has 22.1 years of GPS daily solutions. The spectral indices range from ---0.12 to ---0.92, while the median values of global spectral indices are equal to: ---0.41 ? 0.15, ---0.38 ? 0.12 and ---0.33 ? 0.18 for North, East and Up components, respectively. All non-modelled geophysical processes or non-included artificial effects in time series lead to an underestimation of errors of velocities, but also to changes in the velocity values themselves. The proposed assumption of seasonals subtraction caused the Akaike information criterion values to show a decrease in the median value of 30 %, which in fact means that all the seasonals mentioned here must be taken into account when analyzing noises. Finally, we noticed that there are some of the GPS stations that improved their velocity uncertainty even of 56 %.

GPS derived Zenith Total Delay (ZTD) observed at tropical locations in South India during atmospheric storms and depressions

Global Positioning System (GPS) monitoring of Zenith Total Delay (ZTD) of the troposphere which is related to water vapor is important as it may help us in weather forecasting. The atmospheric water vapor varies according to the season and it also varies quickly on short temporal and spatial scales during stormy periods. Thus it plays a crucial role in meteorology. GPS is one of the relatively inexpensive tools available to monitor the water vapor content in the atmosphere. In the present study, the efficacy of GPS data to monitor perturbations in tropospheric water content (GPS meteorology) associated with atmospheric storms and depressions is investigated utilizing the data from a tropical region of India, recorded between 15th October, 2010 and 27th December, 2010 during which Southern India was affected by a few significant atmospheric events. The ZTD was estimated for this period at the NGRI operated GPS stations at Hyderabad (HYDE) and MS University, Tirunelveli (MSUN). The accuracy of GPS derived ZTD was validated from the close match seen with ZTD values estimated from numerical weather modeling data. During the stormy periods there were strong variations of the ZTD. Corresponding changes in precipitable water vapor were estimated for the International GNSS Service station HYDE. The average ZTD was found to be higher near the coastal station at MSUN and less at the inland station HYDE. Most of the observed peaks in the ZTD time series were well correlated to the atmospheric events that influenced the region. The study extended to two more locations in the equatorial Indian Ocean region showed spatial variations in the ZTD values, which suggest the weakening of ZTD towards the coast. Our observations are yet another illustration for the application of GPS observations to monitor tropospheric water content variations associated with severe atmospheric events.

Geodynamics of the Indian Lithospheric Plate relative to the neighbouring Plates as revealed by Space Geodetic Measurements

Abstract. The Indian Plate is highly dynamic in nature which in turn makes the Indo-Eurassian collision zone the foci of most of the historic large magnitude earthquakes. Processing of positional information from continuously observing reference stations is one of the space based geodetic techniques used globally and nationally to understand the crustal dynamics. The present study evaluates the dynamic nature of the Indian plate relative to its adjoining plates using the permanent GPS data (2011 to 2013) of 12 International GNSS Service (IGS), which are spread across the Indian, Eurassian, Australian, Somaliyan and African plates. The data processing was carried out using GAMIT/GLOBK software. The results indicate that the average velocity for the two IGS stations on the Indian Plate (Hyderabad and Bangalore) is 54.25 mm/year towards NE in the ITRF-2008 reference frame. The relative velocity of various stations with respect to the Indian plate has been estimated using the Bangalore station and has been found that the stations in the Eurasian plate (Lhasa, Urumqi, Bishkek and Kitab) are moving with velocity ranging from 25 to 33 mm/year in the SE direction resulting in compressional interaction with the Indian plate. This study reveals and confirms to the previous studies that the Indian- Eurassian-Australian Plates are moving at different relative velocities leading to compressional regimes at their margins leading to seismicity in these zones.

Integrity monitoring of fixed ambiguity Precise Point Positioning (PPP) solutions

Traditional positioning methods, such as conventional Real Time Kinematic (cRTK) rely upon local reference networks to enable users to achieve high-accuracy positioning. The need for such relatively dense networks has significant cost implications. Precise Point Positioning (PPP) on the other hand is a positioning method capable of centimeter-level positioning without the need for such local networks, hence providing significant cost benefits especially in remote areas. This paper presents the state-of-the-art PPP method using both GPS and GLONASS measurements to estimate the float position solution before attempting to resolve GPS integer ambiguities. Integrity monitoring is carried out using the Imperial College Carrier-phase Receiver Autonomous Integrity Monitoring method. A new method to detect and exclude GPS base-satellite failures is developed. A base-satellite is a satellite whose measurements are differenced from other satellite’s measurements when using between-satellite-differenced measurements to estimate position. The failure detection and exclusion methods are tested using static GNSS data recorded by International GNSS Service stations both in static and dynamic processing modes. The results show that failure detection can be achieved in all cases tested and failure exclusion can be achieved for static cases. In the kinematic processing cases, failure exclusion is more difficult because the higher noise in the measurement residuals increases the difficulty to distinguish between failures associated with the base-satellite and other satellites.