Improving GNSS data analysis with undifferenced integer ambiguity resolution

The study of climate change is an important field of research. Monitoring of atmospheric variability especially the tropospheric precipitable water vapor (PWV) is a powerful way to investigate climate change. Global navigation satellite systems (GNSS) provide a good tool for studying atmospheric parameters as GNSS signals along its path from the satellites to the ground based receivers suffer a significant delay due to the refractivity of earth’s atmosphere. GNSS signals are not only delayed but also refracted in the neutral atmosphere. The zenith wet delays (ZWD) caused by the troposphere can be estimated during the geodetic processing of GNSS signals. Since the ZWD is tightly correlated to the PWV, GNSS observations can be used to study the changes of PWV. In this study GNSS data from the Egyptian permanent GNSS network (EPGN), International GNSS Service (IGS), EUREF Permanent Network (EPN) and Scripps Orbit and Permanent Array Center (SOPAC), for the years 2013 and 2014, were used. These GNSS stations provided a good geometrical coverage over the respective region. All GNSS data were processed using Bernese V 5.2 software. The needed product from GNSS data processing is the tropospheric zenith total delay (ZTD) over each GNSS site. The ZTD is divided based on physical parameters into zenith hydrostatic delay (ZHD) and zenith wet delay (ZWD). The ZWD is the basic observable used to calculate PWV. The values of the PWV were calculated and its variation over the study area was investigated. The quality of calculated PWV values from GNSS data evaluated against traditional Radiosonde (RS) measurements. The results of GNSS PWV showed good agreement with RS PWV when the PWV values were low, but this agreement became worse at high PWV values as the differences between the two techniques increased. The correlation coefficient between RS PWV and GNSS PWV varied from 0.31 to 0.84. Standard deviation of the differences between RS PWV and GNSS PWV ranged from 2.369 to 5.973 mm. The PWV estimated from GNSS observations had annual cycle, and its cycle in 2013 was different from that in 2014. The PWV differences between the 2 years clarified that the water vapor content over the east Mediterranean in most of 2014 days was higher than that in 2013. Furthermore, PWV variations were noted on both temporal and spatial scales. The highest temporal variation value was 25.41 mm whereas the maximum value of the spatial variation was 19.67 mm. The present study illustrated the importance of using geodetic networks to provide atmospheric information.

Wide-lane (WL) uncalibrated phase delay (UPD) is usually derived from Melbourne–Wübbena (MW) linear combination and is a prerequisite in Global Navigation Satellite Systems (GNSS) precise point positioning (PPP) ambiguity resolution (AR). MW is a linear combination of pseudorange and phase, and the accuracy is limited by the larger pseudorange noise which is about one hundred times of the carrier phase noise. However, there exist inconsistent pseudorange biases which may have detrimental effect on the WL UPD estimation, and further degrade user-side ambiguity fixing. Currently, only the large part of pseudorange biases, e.g., the differential code bias (DCB), are available and corrected in PPP-AR, while the receiver-type-dependent biases have not yet been considered. Ignoring such kind of bias, which could be up to 20 cm, will cause the ambiguity fixing failure, or even worse, the incorrect ambiguity fixing. In this study, we demonstrate the receiver-type-dependent WL UPD biases and investigate their temporal and spatial stability, and further propose the method to precisely estimate these biases and apply the corrections to improve the user-side PPP-AR. Using a large data set of 1560 GNSS stations during a 30-day period, we demonstrate that the WL UPD deviations among different types of receivers can reach ± 0.3 cycles. It is also shown that such kind of deviations can be calibrated with a precision of about 0.03 cycles for all Global Positioning System (GPS) satellites. On the user side, ignoring the receiver-dependent UPD deviation can cause significant positioning error up to 10 cm. By correcting the deviations, the positioning performance can be improved by up to 50%, and the fixing rate can also be improved by 10%. This study demonstrates that for the precise and reliable PPP-AR, the receiver-dependent UPD deviations cannot be ignored and have to be handled.

Ground-based GNSS ZTD/IWV estimation system for numerical weather prediction in challenging weather conditions

Acousto-optic devices using lead molybdate and related compounds: Bell Telephone Labs Inc US patent 3617931 (1971) filed 5 May 1969

The fusion of global navigation satellite system (GNSS) and interferometric synthetic aperture radar (InSAR) deformation data can leverage the advantages of GNSS high temporal resolution and InSAR high spatial resolution, and obtain more abundant deformation data for constraints on geophysical structural and mechanical parameters. Existing studies seldom consider the spatial heterogeneity of largescale deformation data, which easily leads to obvious spatial aggregation of errors in the results of fusion. Here, we propose a novel multiresolution segmentation fusion (MRSF) method that uses a multiresolution segmentation algorithm to automatically classify the spatial heterogeneity of InSAR deformation data with similar deformation characteristics. We applied the MRSF method to the fusion of GNSS and InSAR deformation data covering the central valley aquifer system (CVAS) in southern California to verify its precision and robustness. Results show that the MRSF method can accurately reflect spatiotemporal evolution characteristics of displacement data and reliably estimate deformation for the times and locations of missing data. We then tested this method for geophysical parameter estimation by constructing three different sets of data, including dense GNSS sites, sparse GNSS sites, and sparse GNSS sites fused with InSAR data using MRSF, to invert the slip distribution of the Cascadia subduction zone. Results show that the inverted slip of the fused InSAR and GNSS data is comparable to that of the dense GNSS sites. Therefore, the MRSF method can obtain deformation results with high precision and high spatiotemporal resolution and effectively compensate for the lack of data caused by sparse GNSS sites during the geophysical inversion process.

This study proposes a new set of processing procedures based on the strain model and the Kalman filter (SM-Kalman) to obtain high-precision three-dimensional surface deformation time series from interferometric synthetic aperture radar (InSAR) and global navigation satellite system (GNSS) data. Implementing the Kalman filter requires the establishment of state and observation equations. In the time domain, the state equation is generated by fitting the pre-existing deformation time series based on a deformation model containing linear and seasonal terms. In the space domain, the observation equation is established with the assistance of the strain model to realize the spatial combination of InSAR and GNSS observation data at each moment. Benefiting from the application of the Kalman filter, InSAR and GNSS data at different moments can be synchronized. The time and measurement update steps are performed dynamically to generate a 3-D deformation time series with high precision and a high resolution in the temporal and spatial domains. Sentinel-1 SAR and GNSS datasets in the Los Angeles area are used to verify the effectiveness of the proposed method. The datasets include twenty-seven ascending track SAR images, thirty-four descending track SAR images and the daily time series of forty-eight GNSS stations from January 2016 to November 2018. The experimental result demonstrates that the proposed SM-Kalman method can produce high-precision deformation results at the millimeter level and provide two types of 3-D deformation time series with the same temporal resolution as InSAR or GNSS observations according to the needs of users. The new method achieves a high degree of temporal and spatial fusion of GNSS and InSAR data.

The Quasi-Zenith Satellite System (QZSS), which offered positioning signals into your navigation system of devices such as cars and smartphones started service as a four-satellite system from November 2018. They are expected a widespread various innovative services with highly precise positioning. In this study, we describe the development of information processing technology in utilizing Global Navigation Satellite System (GNSS) data in view of the trend of human sensing technology on a wide area outdoor environment. The practical case of target is a human behavior of a skier in ski resort which is case of sports field by GNSS data capture experiment. The behavior of the skier is not only when skiing. There are various actions such as taking a break and ride on a ski lift. That is to say, it is necessary to separate skiing data and other data. In order to realize this, we analyzed the features of the raw GNSS data. We described an analysis of three-dimension GNSS data that is latitude, longitude, high data. As a result, we considered characteristic noise detection results of the data, and extracted of the ski lift ride situation about human behavior analysis.

High precision Global Navigation Satellite Systems (GNSS) positioning and time transfer require correcting signal delays, in particular higher‐order ionospheric (I2+) terms. We present a consolidated model to correct second‐ and third‐order terms, geometric bending and differential STEC bending effects in GNSS data. The model has been implemented in an online service correcting observations from submitted RINEX files for I2+ effects. We performed GNSS data processing with and without including I2+ corrections, in order to investigate the impact of I2+ corrections on GNSS products. We selected three time periods representing different ionospheric conditions. We used GPS and GLONASS observations from a global network and two regional networks in Poland and Brazil. We estimated satellite orbits, satellite clock corrections, Earth rotation parameters, troposphere delays, horizontal gradients, and receiver positions using global GNSS solution, Real‐Time Kinematic (RTK), and Precise Point Positioning (PPP) techniques. The satellite‐related products captured most of the impact of I2+ corrections, with the magnitude up to 2 cm for clock corrections, 1 cm for the along‐ and cross‐track orbit components, and below 5 mm for the radial component. The impact of I2+ on troposphere products turned out to be insignificant in general. I2+ corrections had limited influence on the performance of ambiguity resolution and the reliability of RTK positioning. Finally, we found that I2+ corrections caused a systematic shift in the coordinate domain that was time‐ and region‐dependent and reached up to −11 mm for the north component of the Brazilian stations during the most active ionospheric conditions.

<p><span><span>Global Navigation Satellite Systems (GNSS) play a critical role for providing real-time positioning and navigation services, and the precise satellite orbit and clock products are essential for the high-precision GNSS applications. The International GNSS Service (IGS) and its Analysis Centers (ACs) have been working on the study on precise GNSS data processing and provision of the precise products. The German Research Center for Geosciences (GFZ), as one of the ACs, also provides the multi-GNSS rapid products: the GBM product. We introduce the GBM data processing strategy, analyze the precision of GBM multi-GNSS orbits from 2015 to 2021, and present the impact of applying the undifferenced ambiguity resolution on satellite orbits. The GPS orbits of GBM products agree with the IGS final orbits at the level of 11-13 mm in the three directions, and the GPS orbit 6-hour prediction precision is around 6 cm. The 6-hour prediction precision of GLONASS is around 12 cm, slightly worse than that of GALILEO, which hold an average value of 10 cm in the same period but shows a significant improvement to around 5 cm after end of 2016. The prediction precision of BDS MEO satellites are around 10 cm, and that of the BDS GEO satellites and QZSS satellites are at the level of 1 to 3 meter. The Satellite Laser Ranging (SLR) residuals show that the orbit precision of GALILEO, GLONASS, and BD3-MEO is 23 mm, 41 mm, and 47 mm, respectively. Moreover, comparing the double-differenced ambiguity resolution, adopting the undifferenced ambiguity resolution improves the 6-hour orbit prediction precision by 9-15%</span></span>，<span><span>15-18%</span></span>，<span><span>11-13%</span></span>，<span><span>6-17%</span></span>和<span><span>14-25% for the GPS, GLONASS, GALILEO, BDS-2 and BDS-3 MEO satellites, respectively.</span></span></p>

Temporal mass variations within the Earth’s system can be detected on a regional/global scale using GRACE (Gravity Recovery and Climate Experiment) and GRACE Follow-On (GRACE-FO) satellite missions’ data, while GNSS (Global Navigation Satellite System) data can be used to detect those variations on a local scale. The aim of this study is to investigate the usefulness of national GNSS CORS (Continuously Operating Reference Stations) networks for the determination of those temporal mass variations and for improving GRACE/GRACE-FO solutions. The area of Poland was chosen as a study area. Temporal variations of equivalent water thickness ΔEWT and vertical deformations of the Earth’s surface Δh were determined at the sites of the ASG-EUPOS (Active Geodetic Network of the European Position Determination System) CORS network using GRACE/GRACE-FO-based GGMs and GNSS data. Moreover, combined solutions of ΔEWT were developed by combining ΔEWT obtained from GNSS data with the corresponding ones determined from GRACE satellite mission data. Strong correlations (correlation coefficients ranging from 0.6 to 0.9) between detrended Δh determined from GRACE/GRACE-FO satellite mission data and the corresponding ones from GNSS data were observed at 93% of the GNSS stations investigated. Furthermore, for the determination of temporal mass variations, GNSS data from CORS network stations provide valuable information complementary to GRACE satellite mission data.

<p>Numerous active low Earth orbiters (LEOs) and Global Navigation Satellite System (GNSS) satellites, including the Galileo constellation, are equipped with laser retroreflectors used for Satellite Laser Ranging (SLR). Moreover, most of LEOs are equipped with GNSS receivers for precise orbit determination. SLR measurements to LEOs, GNSS, and geodetic satellites vary in terms of the number of registered normal points (NPs) or registered satellite passes. In 2016-2018, SLR measurements to LEOs constituted 81% of all NPs and 59% of all registered satellite passes, whereas 10% of NPs and 30% of satellite passes, respectively, were assigned to GNSS. The remaining SLR measurements were completed by geodetic satellites, including LAGEOS-1/2, and LARES-1.</p><p>In this study, we show that the SLR observations to Galileo, passive geodetic and active LEO satellites together with precise GNSS-based orbits of LEOs and Galileo, can be used for the determination of global geodetic parameters, such as geocenter coordinates (GCC) and Earth rotation parameters (ERPs), i.e. pole coordinates, and length-of-day parameter.</p><p>GCC are typically determined using SLR observations to passive geodetic satellites, such as LAGEOS-1/2. Also, the SLR observations to LAGEOS-1/2 together with GNSS and Very Long Baseline Interferometry data are used for the determination of ERPs. Here, we use SLR observations to Galileo, LAGEOS-1/2, LARES-1, Sentinel-3A, SWARM-A/B/C, TerraSAR-X, Jason-2, GRACE-A/B satellites to investigate whether they can be applied for the reference frame realization and for deriving high-quality global geodetic parameters.</p><p>We present various types of solutions to investigate the best solution set-up. The studied solutions differ in terms of solution lengths, the combination of different sets of satellites and the relative weights for the variance scaling factors of technique and satellite-specific normal equations. We compare our results with the standard LAGEOS-based solutions, the combined EOP-14-C04 products and show the consistency of the results.</p>

With the capability to record Global Navigation Satellite Systems (GNSS) data at high-rate, at sampling rates typical for seismological applications, experiments are needed to quantify the response of GNSS to shaking from earthquakes. There have been a few studies that examine the response of GNSS to strong shaking. Recently, Ebinuma and Kato (2012) used a global positioning system (GPS) simulator to electronically test several GNSS receivers and obtain the receiver characteristics at three frequencies: 1, 2, and 5 Hz. The results showed that the amplitude of 5-Hz displacements recorded by the GPS was, depending on the receiver model, between 30 and 125 percent more than the displacement input to the simulator. At low frequencies, the GPS displacement was nearly equal to the input displacement. In addition, Ebinuma and Kato (2012) examined how each receiver model amplified an earthquake displacement record in the 2–8 Hz band. The study discussed here builds on the tests by Ebinuma and Kato (2012), but rather than using electronic simulation, the tests are setup outdoors and closer to actual field installations of GNSS equipment. The authors used a one-dimensional shake table capable of 400 mm of displacement and high acceleration; the shake table also is constrained by a precision linear slider to have very low tilt that would affect inertial sensors. In addition, the stage position can be accurately monitored independent of the GNSS hardware and, importantly, provides a reference to compare with the estimated displacements from the GNSS data. The tests spanned a greater frequency range from 0.2 to 20 Hz and used equipment from three different manufacturers covering five different combinations of receivers and antennas. In addition, the authors have been able to simulate the frequency response of the GNSS equipment using a simple, causal filter. The quality of the filter was tested using additional test data where a step function in displacement was applied to the shake table. The observed displacements from the GNSS data show an overshoot in displacement at the time of the step or transition of the stage. That overshoot was accurately predicted using the filter design derived from the sinusoidal displacement tests.

Implementing the International GNSS Service 2021+ Strategic Plan: Vision and Use Cases

The International GNSS Service (IGS) is an international activity involving more than 200 participating organisations in over 80 countries with a track record of one and a half decades of successful operations. The IGS is a service of the International Association of Geodesy (IAG). It primarily supports scientific research based on highly precise and accurate Earth observations using the technologies of Global Navigation Satellite Systems (GNSS), primarily the US Global Positioning System (GPS). The mission of the IGS is “to provide the highest-quality GNSS data and products in support of the terrestrial reference frame, Earth rotation, Earth observation and research, positioning, navigation and timing and other applications that benefit society”. The IGS will continue to support the IAG’s initiative to coordinate cross-technique global geodesy for the next decade, via the development of the Global Geodetic Observing System (GGOS), which focuses on the needs of global geodesy at the mm-level. IGS activities are fundamental to scientific disciplines related to climate, weather, sea level change, and space weather. The IGS also supports many other applications, including precise navigation, machine automation, and surveying and mapping. This article discusses the IGS Strategic Plan and future directions of the globally-coordinated ~400 station IGS network, tracking data and information products, and outlines the scope of a few of its numerous working groups and pilot projects as the world anticipates a truly multi-system GNSS in the coming decade.

Abstract. The spatiotemporal variations of integrated precipitable water vapor (IPWV) are very important in understanding the regional variability of water vapor. Traditional in situ measurements of IPWV in the Indian region are limited, and therefore the performance of satellite and Copernicus Atmosphere Meteorological Service (CAMS) retrievals with the Indian Global Navigation Satellite System (GNSS) as reference were analyzed. In this study the CAMS reanalysis data of 1 year (2018) and the Indian GNSS and INSAT-3DR sounder retrieval data for 1.5 years (January 2017 to June 2018) were utilized, and statistics were computed. It is noticed that seasonal correlation coefficient (CC) values between INSAT-3DR and Indian GNSS data mainly lie within the range of 0.50 to 0.98 for all the selected 19 stations except Thiruvananthapuram (0.1), Kanyakumari (0.31) and Karaikal (0.15) during the monsoon season and Panjim (0.2) during the post-monsoon season. The seasonal CC values between CAMS and GNSS IPWV range from 0.73 to .99 except for Jaipur (0.16) and Bhubaneswar (0.29) during the pre-monsoon season, Panjim (0.38) during the monsoon season, Nagpur (0.50) during the post-monsoon season, and Dibrugarh (0.49) Jaipur (0.58) and Bhubaneswar (0.16) during the winter season. The root mean square error (RMSE) values are higher under the wet conditions (pre-monsoon and monsoon season) than under dry conditions (post-monsoon and winter season), and we found differences in magnitude and sign of bias for INSAT-3DR and CAMS with respect to GNSS IPWV from station to station and season to season. This study will help to improve understanding and utilization of CAMS and INSAT-3DR data more effectively along with GNSS data over land, coastal and desert locations in terms of the seasonal flow of IPWV, which is an essential integrated variable in forecasting applications.