Global Positioning System Observations Research Articles

Combination of swarm, Jason-3, and GNSS observations to construct a new modeling of global ionospheric maps

By increasing various space geodetic observation techniques with different orbital altitudes the capability for ionosphere layer monitoring is enhanced. In this paper, in order to increase the accuracy and reliability of Global Ionosphere Maps (GIMs) in regions with no or sparse GNSS data coverage, the observational data derived from Swarm, consisting of three Low Earth Orbiter (LEO) satellite constellation missions and a satellite altimetry mission, was integrated with the Global Positioning System (GPS) observations. The vertical total electron content (VTEC) of GPS and Swarm LEO satellites was obtained by employing the modified single-layer mapping function (MSLM) on the slant total electron content (STEC) and then the VTECs derived from three techniques were represented by the Spherical Harmonics (SH) expansion function up to the degree and order 15 in a solar-geomagnetic frame. In regard to the combination of different observation techniques, the systematic biases between different data sources are required to be considered. Here, the systematic biases of Swarm and Jason-3 satellites were expanded in terms of SH function and regarded as unknown parameters for estimation. Moreover, in order to consider different accuracy levels of ionospheric data groups, the Helmert Variance Component Estimation (H-VCE) was used to determine appropriate relative weights of observation groups. The two-dimensional combined models were constructed during 10 days in the period of DOY 271–275, 2017 and DOY 003–007, 2018 by considering different high and low Kp-indexes from 1 to 7 values. The obtained results showed that after adding the Swarm and Jason-3 data to GPS observations, the reduction of mean standard deviation (STD) maps was in the range of about 46–56% in 10 days. The combined method improved the reliability and precision of GIMs in oceanic regions significantly. However, the impact of VTECs from Swarm satellites was higher than that of VTECs from satellite altimetry due to the appropriate data sampling and coverage of Swarm mission. The results are also validated against the VTECs derived from 5 IGS stations (that are not included in the modeling). Our results indicate that the Combined method's mean Root Mean Square Error (RMSE) compared to GNSS dual-frequency measurements were less than 1.6 TECU with an improvement of about 9.56–25.80% respect to the mean RMSE of GIMs constructed by only GPS measurements.

Assessment of machine learning techniques for prediction of integrated water vapor using meteorological data

Weather and Climatological studies are very important in assessing atmospheric conditions like storms and cyclones. Integrated water vapor (IWV) is an important greenhouse gas in the atmosphere responsible for the Earth's radiative balance. Global Positioning System (GPS) observations have been used for monitoring the IWV variability. The IWV estimations are carried out using ground-based GPS observations at Hyderabad (17.4°N, 78.46°E), India using GAMIT software. GAMIT is GPS analysis software developed by MIT, USA. It takes input as GPS observation data containing pseudo ranges, navigation data containing ephemeris, clock errors, g-files with orbital information, and meteorological data like pressure, temperature, and relative humidity to calculate IWV. However, estimating IWV for forecasting applications is impossible with a GPS system. This paper introduces a methodology to predict IWV during normal days and severe cyclonic events using machine learning (ML) techniques. Rational quadratic Gaussian process regression (RQ-GPR) and neural network (NN) algorithms are considered for identifying suitable ML prediction algorithms over tropical conditions. Meteorological surface data like Pressure, Temperature, and relative humidity are given as input to the machine learning models. The IWV values computed from GPS are compared with the model's predicted values. RQ-GPR model is showing good accuracy with the IWV values computed from GPS against the NN model. The correlation coefficient (ρ) achieved for RQ-GPR is 0.93, and 0.86 is obtained for the NN model.
 The RMSE (Root Mean Square Error) of the predicted IWV value with RQ-GPR is better than the NN model. We have obtained mean square error (MSE) and mean absolute error (MAE) as 18.146 kg/m2 and 3.0762 kg/m2 for RQ-GPR and 27.509 kg/m2 and 3.9102 kg/m2 for the NN model which is showing RQ-GPR is a suitable model for forecasting applications. The HUDHUD cyclonic event that occurred in October 2014 is considered for testing the proposed ML algorithms. RQ-GPR model has better results in the Prediction of IWV than the NN model. The RMSE value obtained is 2.837 kg/m2 for RQ-GPR and 3.327 kg/m2 obtained from the NN model. The results indicate that the RQ-GPR model has more accuracy than the other IWV prediction models. The prediction results are helpful for meteorology, weather, and climatology studies and useful to improve the accuracy of the regional numerical weather prediction models.

Strong Ground Motion Recorded by High-Rate GPS during the 2021 Ms 6.4 Yangbi, China, Earthquake

Abstract The 2021 Ms 6.4 Yangbi earthquake, Yunnan, China, was recorded by the Dali Global Positioning System (GPS) network comprising 37 permanent stations within 100 km of the epicenter. All of these GPS stations recorded 1 Hz data, and 12 of them also recorded 5 Hz data. Using sophisticated data processing strategies, especially the method to overcome ionospheric and multipath errors, near-field waveforms of epoch-by-epoch displacement of all of the GPS stations within an epicentral distance of ∼50 km were derived from high-rate GPS observations with a root mean square error of 3.8, 4.2, and 8.2 mm for the east–west, north–south, and up components, respectively. The peak ground displacement of up to 14 cm in the horizontal direction and 4.2 cm in the vertical direction and the largest coseismic displacement of 3.1 cm in the horizontal direction and 3.2 cm in the vertical direction were observed for the stations within 6–9 km of the epicenter. The waveforms, with dominant periods between 7 and 10 s, present a systematic change in shape as a function of distance from the source, which demonstrates that the high-rate GPS observations can provide reliable relative-displacement response spectra at the periods needed in the design of large structures for resisting strong earthquakes. Comparisons of the GPS displacement time series at 1, 2.5, and 5 Hz suggest that 5 Hz data are able to capture strong ground information that are of interest to both earthquake seismologists and engineers. We conclude that the displacement waveforms and motion trajectories from high-rate GPS observations provide unique additional information of the near-field strong ground motion that is valuable to seismologists in unraveling the dynamic process of fault rupture and to engineers for designing large structures with very long period response.

Assessment of ZTD Derived from COSMIC Occultation Data with ECWMF, Radiosondes, and GNSS.

Global Navigation Satellite System (GNSS) signals generate slant tropospheric delays when they pass through the atmosphere, which is recognized as the main source of error in many spatial geodetic applications. The zenith tropospheric delay (ZTD) derived from radio occultation data is of great significance to atmospheric research and meteorology and needs to be assessed in the use of precision positioning. Based on the atmPrf, sonPrf, and echPrf data from the Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) Data Analysis and Archiving Center (CDAAC) from 1 January to 31 December 2008 and 2012, we obtained the ZTDs of the radio occultation data (occZTD) and the corresponding radiosonde (sonZTD) and ECWMF data (echZTD). The ZTDs derived from ground-based global positioning system (GPS) observations from the International GNSS Service (IGS) were corrected to the lowest tangent point height of the matched radio occultation profile by the barometric height formula (gnsZTD). The statistical results show that the absolute values of the bias between occZTD and echZTD, sonZTD, or gnsZTD are less than 5 mm, and the standard deviations are approximately 20 mm or less, indicating that occZTD had significant accuracy in the GNSS positioning model even when the local spherical symmetry assumption error was introduced when the Abel inversion algorithm was used to obtain the refractive index profile of atmPrf. The effects of the horizontal/vertical matching resolution and the variation in the station height/latitude on the biases of occZTD and gnsZTD were analyzed. The results can be used to quantify the performance of radio occultation data for tropospheric delay error correction in dynamic high-precision positioning.

Stress and Strain Characteristics before the Mw 7.3 Maduo Earthquake and Its Implications for Future Earthquakes on the Maqin–Maqu Fault

ABSTRACT To determine the crustal deformation and the stress–strain accumulation characteristics preceding the Mw 7.3 Maduo earthquake and the seismic potential of the Maqin–Maqu fault segment, the seismic data from small earthquake events and Global Positioning System (GPS) observations stations are collected. The b-value, the GPS velocity field, the GPS baseline, and the GPS strain parameters for multiple areas are calculated and analyzed. The results show a low b-value anomaly in the epicenter and its adjacent areas before the earthquake, which suggest that the stress level of the medium in this area was high before the earthquake. The regional GPS velocity field indicates that the earthquake epicenter is in an area where strain energy accumulates at varying slip rates and orientations. The deformation rates of the northeast-oriented baselines on the east side of the fault and the northwest-oriented baselines on the west side of the fault are lower than those observed near the three near north–south-oriented baselines, reflecting a small compressive deformation that occurred at the epicenter before the earthquake. Meanwhile, the motion of baselines QHYS-QHMD, QHYS-QHMQ, and QHGE-SCSP noticeably decreased, indicating that the area near the fault had already stored a great deal of strain energy prior to the earthquake. The rate of plane strain reduced in the epicenter region before the earthquake gradually since the second half of 2019, illustrating the deficit points to high stress conditions in the epicenter area. Furthermore, the area near the epicenter was characterized by high strain accumulation before the earthquake. The Maqin–Maqu segment of the East Kunlun fault is likely to be capable of generating strong earthquakes in the near future, because the current state of the area is similar to that of the Maduo epicenter before the onset of the earthquake.

Comparison of Two Corrector Surface Models of Orthometric Heights from GPS/Levelling Observations and Global Gravity Model

The advent of space-based measurement systems such as the Global Positioning System (GPS) offers a new alternative in orthometric height determination over conventional spirit levelling. The ellipsoidal height (h) obtained from GPS observations can be transformed into orthometric height if the geoid undulation (N) is known from a national gravimetric geoid model. However, the lack of a national geoid model in Nigeria hinders the use of the method. This study compares two corrector surface models of orthometric heights from GPS/levelling observations and the Global Gravity Model. Model A (7-parameter) and Model B (8-parameter) are based on the general 7-parameter similarity datum shift transformation. A network of twenty-one (21) GPS/levelling benchmarks within the study area were used and their geoidal heights were computed using GeoidEval utility software with reference to Global Gravitational Model (EGM08). Least squares adjustment was used to compute the coefficients of the models. Root mean square error (RMSE) was used to assess the accuracy of the models with model A having RMSE=0.171m and model B having RMSE=0.169m. Model B with the lowest RMSE is hence the better of the two models. The t-test and hypothesis test conducted at a 95% confidence level, however, revealed that the two models did not differ significantly. The study shows that the use of corrective surface to combine the gravity field model EGM08 and GPS/levelling significantly improves the determination of heights as observed from GPS in the study area.

Comparative Analysis of Smartphones and Survey-Grade GNSS Receivers for Parcel Boundary Determination

This paper advances the existing body of knowledge on the suitability of accuracy derivable from the use of smartphones for cadastral mapping. Zenvus App software was installed on two smartphones of a different make. A set of dual-frequency GPS Promark 3 receivers and two different smartphones of different make were used for data acquisition. Observations were carried out at the boundaries of ten parcels of land, comprising 46 boundary points. Coordinates of these points were obtained using Differential Global Positioning System (DGPS) observation in static mode and two android smartphones (Samsung A70 and Tecno Spark 3 Pro). Mean score, root means square error, and one-way analysis of variance was used to show significant differences in the equipment used. Overall, both the accuracy (mean) and precision (RMSE) were lower than those obtained by Differential GPS. A one-way analysis of variance (ANOVA) was calculated on the values of both X and Y. For X, the analysis was not significant, F (1, 45)= 0.88, p= 0.419 and for Y, the analysis was also not significant, F(1,45) =0.97, p=0.383. The total RMSE shows that coordinates of points as obtained by the Samsung smartphone (3.368) was more precise than Tecno (4.041). However, the two smartphones (Tecno and Samsung) were less accurate than differential GPS. This implies that there is a 95% chance that the errors in the estimates are less than 6.993m (for Tecno) and 5.848m (for Samsung) respectively. The variation in the observations obtainable with smartphones affects both linear and polygon estimates. The study concluded that the magnitude of these errors is significant in cadastral survey practices and hence not suitable for use. It is recommended that further studies be carried out on the use of the Zenvus app on centimeter grade smartphones probably this could yield a better result suitable for cadastral mapping.

Long-term correlation analysis between monthly precipitable water vapor and precipitation using GPS data over China

Precipitable Water Vapor (PWV) is an important driving factor for the occurrence of precipitation. A deep understanding of the correlation between the PWV and the precipitation helps to understand the regional water cycle based on the theory of atmospheric water balance. This study aims to analyze the correlation between the precipitation and the PWV derived from Global Positioning System (GPS) observations collected from a total of 233 Global Navigation Satellite System (GNSS) stations in China mainland over 10 years. The PWV was calculated through Zenith Total Delay (ZTD) from the Precise Point Positioning (PPP) technique and metrological data from the European Centre for Medium-Range Weather Forecasts (ECMWF). The relationship between PWV derived from GPS and the precipitation from the Tropical Rainfall Measuring Mission (TRMM) at monthly temporal resolution was analyzed through the cross-correlation analysis and the cross-wavelet analysis. Results showes that a 1-month lag was observed between monthly PWV and precipitation at some inland stations in the south-eastern region of China, which is due to the earlier peaks of precipitation caused by the quasi-stationary front in this region. After the time-lag shift, most of the stations showed a cross-correlation coefficient higher than 0.7, indicating that monthly PWV and precipitation are generally correlated over China mainland. Specifically, the cross-correlation coefficients from stations located in western China have a wide range of 0.16–0.95 and a large dispersion degree with the standard deviation (STD) of 0.2, which is due to the variable climatic conditions caused by the topographical distribution. The cross-correlation coefficients from stations located in the middle and north-eastern region of China are generally greater than 0.75 and have an STD of 0.08, while those located in the south-eastern region of China are generally less than 0.65 and have an STD of 0.09. This is because the south-eastern region of China has a relatively longer rainy season caused by the influences from Asian monsoon systems. These results could contribute to the further understanding of the regional water cycle based on the theory of atmospheric water balance within China.

Estimation of GPS transmitter antenna phase center offsets by integrating space-based GPS observations

The deviations of the microwave signal transmitting point of Global Navigation Satellite Systems (GNSS) satellites with respect to the corresponding center-of-mass were and still are significant bias sources for GNSS-based terrestrial reference frames (TRF). Satellite phase center offsets (PCOs) and variations (PVs) are usually derived from GNSS observations from the tracking network of the International GNSS Service (IGS). Because of the strong correlation between the scale of the TRF and the satellite PCOs in the z-direction (z-PCOs), a no-net-scale (NNT) condition relative to, for instance, the International Terrestrial Reference Frame (ITRF) is commonly applied. One approach for estimating transmitter phase centers without constraining the scale is to consider space-based GNSS observations. Within this study, we estimate the satellite PCOs of the Global Positioning System (GPS) based on zero-difference ionosphere-free observations from six low Earth orbiters (LEOs) and ground networks with different numbers of stations. The six LEOs are different in their orbits, GPS receiver equipment, and tracking characteristics. We jointly estimate orbits, station coordinates, and GPS satellite PCOs in an integrated processing. The horizontal offsets are shown to significantly benefit from the LEOs onboard observations by reducing the correlation between these offsets and the GPS satellite orbit and attitude. Without applying a no-net-scale condition to the ground network, the GPS z-PCOs are estimated. By adding six LEOs, the correlation coefficients between the GPS z-PCOs and the scale is reduced significantly (about from 0.85 to 0.3), consequently, the precision of estimation is improved. When including the six LEOs, the GPS z-PCOs estimated without applying NNS are very stable. The estimated GPS z-PCOs have a −231 mm difference in average to the values in igs14_2134.atx and the corresponding scale to IGS14 reference frame is +1.89 part per billion. The estimated GPS z-PCOs agree with previous studies based on Swarm satellites and Galileo. The improvement due to different numbers of LEOs and the impact of LEO z-PCO errors on the estimation are discussed.

GPS observations of ionospheric TEC variations over Nepal during 22 July 2009 solar eclipse

As the study of ionospheric behavior during various solar activities is an important task, various studies of ionospheric changes during eclipse events have been widely performed in the different regions of the globe. This paper investigates the ionospheric responses to the solar eclipse on 22 July 2009 over Nepal using the total electron content (TEC) measured by dual-frequency Global Positioning System (GPS) receivers. The time-averaged Vertical TEC (vTEC) of ten GPS stations from Nepal is analyzed and it is found that the value of ionospheric TEC decreases due to the reduction of ionizing radiation. In addition, the deviation in the TEC value on eclipse day from the mean vTEC value of the top five quietest days is found to lie in the range ~1–5 TECu at those regions which were associated with the partial eclipse shadow. On the other hand, the region with the total eclipse (BRN2 and RMTE) faced ~6–7 TECu on average reduction in the TEC value. Considering that the eclipse of 22 July 2009 occurred just at sunrise in the Nepalese zone, a maximum reduction of about 5 TECu is very significant. Higher deviation in TEC is therefore linked with the path of totality and the obscuration rate. This study reveals that the ionospheric TEC over Nepal was altered by wave-like energy and momentum transport, as well as obscuration of the solar disc due to the partial and total solar eclipse. Furthermore, the cross-correlation results presented similar type signatures of the eclipse-induced ionospheric modification over Nepal. This research work serves a crucial future reference for the comparative study of change of ionospheric TEC variability over the Nepal region during Eclipse events

Acceleration of Deep Slip Along the Longmenshan Fault Plane Before the 2008 M8.0 Wenchuan Earthquake

The first step toward earthquake forecasting is the identification of variables whose spatio-temporal variation can be connected with pre-seismic crustal deformation. Four periods of campaign Global Positioning System (GPS) observations around the Longmenshan fault zone (LFZ) provide important insights in crustal deformation and deep fault slip before the 2008 M8.0 Wenchuan earthquake. By using TDEFNODE to invert the coupling fraction and dynamic slip deficit rate of the Longmenshan fault plane before the Wenchuan earthquake, we show that under a background of strong coupling, the compressive slip deficit rate perpendicular to fault increased slightly at first and then decreased; a value of ∼1.5–3.6 mm/a along the central–southern segment from 1999 to 2001 increased to ∼1.9–3.9 mm/a from 2001 to 2004, and then decreased to ∼1.1–2.6 mm/a from 2004 to 2007. The dextral slip deficit rate parallel to fault was ∼6 mm/a from 1999 to 2004, before increasing significantly to ∼9.5 mm/a from 2004 to 2007, when the compressive slip deficit rate decreased. At the same time, large-scale GPS velocity profiles show that compressive shortening deformation in the Eastern Tibet Block, perpendicular to fault, increased slightly from 2001 to 2004, and then decreased from 2004 to 2007. Meanwhile, the dextral shear deformation parallel to fault near the LFZ increased significantly from 2004 to 2007. These findings are in good agreement with those calculated using repeating earthquake sequences, indicating that the deep slip rate of the Longmenshan fault plane may have accelerated several years before the Wenchuan earthquake. Our results demonstrate that GPS data can record pre-seismic preparatory processes, and have the potential for use in medium-term large earthquake forecasting.

Assessment of the performance of GPS/Galileo PPP-RTK convergence using ionospheric corrections from networks with different scales

The rapid convergence of precise point positioning real-time kinematics (PPP-RTK) with centimeter-level accuracy is of utmost importance for many applications. One way of accelerating this convergence is to explore the use of ionospheric models and multiple global navigation satellite system (GNSS) observations, e.g., Global Positioning System (GPS) and Galileo Satellite Navigation System (Galileo) observations. Because the temporal and spatial variations of the ionosphere are significant, convergence analysis of PPP-RTK should be investigated in networks with different scales, especially networks with large differences in their scales. This study describes the convergence performance of PPP-RTK using GPS/Galileo observations derived from networks with different scales under medium ionospheric conditions. Slant ionospheric corrections were first estimated from the reference network and then imported as virtual observations to enhance the convergence performance of PPP-RTK at the user interface. The results show that for the 165-km reference site spacing, the portions of single-differenced (SD) ionospheric residuals within 0.3 total electron content units (TECU) were 85.2% and 81.7% for the GPS and Galileo observations, respectively. Considering the 90th percentile of horizontal position errors, the PPP-RTK convergence time within the network with 165-km spacing was shortened from 2.5 min for GPS-only observations to 2.0 min for integrated GPS + Galileo observations. For the network of about 50 km, the proportions of the SD ionospheric residuals of the GPS and Galileo constellation within 0.3 TECU were 95.9% and 82.8%, respectively. The PPP-RTK convergence time of the 90th percentile horizontal positioning errors based on GPS-only observations was 2.0 min but 1.5 min based on integrated GPS + Galileo observations. Using GPS and Galileo observations, the convergence time could be reduced by 25% for the network with 50-km spacing. Our results suggest that the convergence time of PPP-RTK depends on the scale of the reference network and becomes shorter as the scale of the network decreases. Compared with the GPS-only PPP-RTK, the GPS/Galileo PPP-RTK could shorten the convergence time further.Graphical

Performance of global navigation satellite systems (GNSS) in absence of GPS observations

Over the last decades, a wide range of applications that require positioning relied on the global positioning system (GPS) established by the US Department of Defence (DOD). However, depending on a single constellation may not be sufficient to guarantee a successful positioning accuracy at any time. Consequently, having several constellations that can be used for positioning offers the opportunity to maintain continuous positioning. This became possible with the global coverage of other constellations such as GLONASS, designed by Russia, Galileo, designed by the European Union, and BeiDou, designed by China. In this research, the accuracy of using each of these constellations individually is assessed and compared to the accuracy obtained from GPS to validate the possibility of using these constellations in positioning in the absence of GPS. For this purpose, Global Navigation Satellite Systems (GNSS) data were collected from five stations in Cairo, Egypt using GNSS receivers. The results indicate that using GLONASS, Galileo, and BeiDou can overcome the problematic periods during GPS signal outages. In addition, the different duration lengths of static positioning results indicate that using GLONASS-only or BeiDou-only for positioning provides less accuracy than GPS-only in both horizontal and vertical directions. Furthermore, as a standalone positioning constellation, Galileo can be used now to replace GPS. Moreover, Galileo, GLONASS, and BeiDou improve the positioning accuracy by 0.007 m over the GPS-only model. Therefore, the solution can reach reliable precision levels that can be exploited for the high-accuracy-demanding postprocessing applications in Egypt and the surrounding area.

Current Slip and Strain Rate Distribution Along the Ganzi-Yushu-Xianshuihe Fault System Based on InSAR and GPS Observations

The Ganzi-Yushu-Xianshuihe fault (GYXSF), a large strike-slip fault located on the east side of the Tibetan Plateau, has seen high seismic activity in recent years. However, despite the earthquake risk posed by this fault, there is a lack of high-resolution geodetic survey results regarding the current slip rate. We have used 4-track ascending and 5-track descending Sentinel-A/B SAR Interferometric Synthetic Aperture Radar (InSAR) data from 2014 to 2020, to obtain the current slip rate of the entire GYXSF within the radar’s line of sight (LOS), with high resolution. Both InSAR and published Global Positioning System (GPS) data were integrated to calculate a high-resolution three-dimensional deformation field and strain rate field of the GYXSF. We have also used the screw dislocation model to calculate current slip rates in the fault-parallel direction at 20 km intervals. The key findings of our study are as follows. (1) The current slip rate of the GYXSF is segmental: the slip rate of the Ganzi-Yushu fault (GYF) gradually increases from ∼1 to ∼6 mm/yr from the north-west to the southeast, while the slip rate of the Xianshuihe fault (XSF) increases from ∼8.5 to ∼12 mm/yr from the north-west to the southeast. (2) There are non-negligible post-earthquake deformations along the GYXSF, and our best fitting results show that an approximately 100 km long section of the GYF has undergone post-seismic after-slip in the 4–10 years since the 2010 Yushu M 6.9 earthquake, with a maximum creep of ∼2.2 mm/yr (3) The strain rate is dispersed in the GYF region but concentrated on the fault in the XSF region. There is also a measurable strain rate on secondary faults north of the GYXSF, implying the seismic hazard of these secondary faults cannot be ignored. (4) The continuous deformation and block-like models are the best models to explain the observations and deformation characteristics of the GYF and XSF, respectively.

Effect of 21 June 2020 solar eclipse on the ionosphere using VLF and GPS observations and modeling

A solar eclipse event provides a great opportunity to examine the behavioral concept of the ionospheric electron density (N e ) variability in the low latitude region. The current work presents our outcomes from the simultaneous assessment of Tweeks (radio atmospherics) and radio signals (fixed frequency of the transmitter's signal) from multifarious VLF transmitters observed at Varanasi (Geog. Lat. 25.27 0 N, Geog. Long. 82.98 0 E, Geomag. Lat. 14 0 55′N). To find the presence of disturbances in the ionosphere Global Positioning System (GPS) data at Hyderabad (geog. lat. 17 0 20 / N, long. 78 0 30 / E) and Bangalore (geog. lat. 12 0 58 / N, long. 77 0 33 / E) is also analyzed during the period of the solar eclipse on 21 June 2020. As the Sun was eclipsed, the nighttime phenomenon of ‘Tweeks' was also observed in the daytime through the annular solar eclipse due to nighttime conditions as the solar disc was dusked. Tweek analysis shows the variation in the ionospheric reflection heights (∼8–11 km) and electron density (∼3–2 cm −3 ) in the D-region during the eclipse. The reflection height of the D-region ionosphere increases from ∼84 km and goes to ∼95 km and then decreases to ∼87 km. Electron concentration (electron density) decreased throughout the eclipse from 24 cm −3 to 21 cm −3 and then increases to 23 cm −3 . Eclipse-imposed modifications in VLF transmitter’s (HWU and NWC) signals displays an average change (decrease) of 2.8 dB and 0.8 dB in the signal strength of 18.3 kHz (HWU) and 19.8 kHz (NWC) transmitters respectively and a rise in virtual reference height (H′) and sharpness factor (β), as compared with normal days. The de-trended value of total electron content (DTEC) variations at both stations clearly shows the presence of travelling ionospheric disturbances (TIDs) having wave-like features. The Fast Fourier Transform (FFT) analysis shows that periodicity at both the station lies in two regimes one belongs to a period between 20 and 50 min and the other belongs to 50–90 min indicating such oscillation observed in the ionosphere are induced by atmospheric gravity waves (AGWs) generated during the period of the solar eclipse.

Sparse Reconstruction of 3-D Regional Ionospheric Tomography Using Data From a Network of GNSS Reference Stations

3-D computerized ionospheric tomography (CIT) is an ill-posed problem due to the insufficient amount of observations, it remains challenging for practical applications. In this article, we proposed an ionospheric tomography method that combined data-driven methods with compressed sensing (CS) to deal with the ill-posed problem. First, slant total electron content (STEC) data were extracted by undifferenced and uncombined precise point positioning (UCPPP) with known fixed station coordinates. Second, data-driven methods were adopted to construct the projection matrix from the ionospheric model. Third, compressed sensing was used to derive the sparse solution based on <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$L_{1}$ </tex-math></inline-formula> norm. The ionospheric tomography can be achieved well by using observations during the shorter time interval and in a sparse receiver distribution based on the property of compressed sensing. Results of experiment based on real Global Positioning System (GPS) observation data verified the effectiveness of the proposed methods. By comparing with the colocated ionosonde, it is found that the CS methods are more consistent with the actual ionospheric fluctuation than the modified constrained algebraic reconstruction technique (CART). In terms of the differential STEC (dSTEC) analysis, the error of the tomography model by Compressed Sensing-Principal Component Analysis (CS-PCA) is less than 0.2 TEC unit (TECU), and the time resolution is 5 min. The UCPPP with constraint by CS-PCA shows the best performance of 12.2%, 40.9% and 0.31% improvement in positioning accuracy, convergence time, and fixed rate over the UCPPP with constraint by modified CART. The proposed data-driven methods may be important for high-resolution 4-D ionospheric tomography in the future.

Detecting aliasing and artifact free co-seismic and tsunamigenic ionospheric perturbations using GPS

• Nonuniform spatial sampling and polynomial misfits introduce aliasing and artifacts in ionospheric perturbations obtained using GPS. • Spatio-Periodic Leveling Algorithm (SPLA) is efficient in removing such aliasing and artifacts. • SPLA detects 50% more perturbations compare to conventional methods and increases SNR up to 149%. • SPLA efficiently detects perturbations at low elevations and removes the need of elevation cut-off. Ionospheric perturbations induced by tsunamis and earthquakes can be used for tsunami early warning and remote sensing of earthquakes, provided the perturbations are characterized properly to distinguish them from the ones caused by other sources. The ionospheric perturbations are increasingly being obtained from Global Positioning System (GPS) based Total Electron Content (TEC) measurements sampled at uniform time intervals. However, the sampling is not uniform in space. The nonuniform spatial sampling along the GPS satellite tracks introduces aliasing if it is not accounted while computing the ionospheric perturbations. All the methods hitherto used to detect the co-seismic and tsunamigenic ionospheric perturbations did not account the nonuniform spatial sampling while computing these perturbations. In addition, the residual approach used to obtain the perturbations by detrending the TEC time series using high-order polynomial fit introduces artifacts. These aliasing and artifacts corrupt amplitude, Signal-to-Noise Ratio (SNR), phase, and frequency of ionospheric perturbations which are vital to distinguish the perturbations induced by tsunamis and earthquakes from the rest. We show that Spatio-Periodic Leveling Algorithm (SPLA) successfully removes such aliasing and artifacts. The efficiency of SPLA in removing the aliases and artifacts is validated under two simulated scenarios, and using GPS observations carried out during two natural disasters – the 2004 Indian Ocean tsunami and the 2015 Nepal-Gorkha earthquake. We, further, studied the severity of aliasing and artifacts on co-seismic and tsunamigenic perturbations by analyzing its characteristics employing SNR, spatiotemporal, and wavelet analyses. The results reveal that removal of aliasing and artifacts using SPLA i) increases the SNR up to ∼149% compared to the residual method and ∼39% compared to the differential method, ii) distinctly resolves signals from sharp static variations, and iii) detects 50% more co-seismic ionospheric perturbations and 25% more tsunami-induced ionospheric perturbations in the two events studied. Cross-correlation of the perturbation time series obtained using the residual method and SPLA reveals that aliasing and artifacts shift the time of occurrence by −7.64 minutes to +4.21 minutes. Further, the results show that the SPLA efficiently detects the ionospheric perturbations at low elevation angles, thereby removes the need of applying elevation cut-off and increases the area of ionospheric exploration of a GPS receiver.

Accuracy Assessment of Different Polynomial Geoid Models in Orthometric Height Determination for Akure, Nigeria

Height is an important component in three dimensional coordinates and determination of the position of points for any meaningful development. Ellipsoidal heights from GNSS require geoid model which could be global, regional and local for transformation to orthometric height. The absence of a national geoid model in Nigeria remains a great drawback to develop local geoid for local application in place of global geoid models. The study aims to assess the accuracy of polynomial geoid models in orthometric height determination. Differential Global Positioning System (DGPS) observations were carried out to determine ellipsoidal heights of the point while nine and eleven coefficients were used for the geoid and orthometric height modelling. Model A and Model C used 2-D (x, y) positions with nine and eleven parameters while model B used 3-D (x, y, ∆h) positions with nine parameters. The least-squares method was adopted in computing the parameters of the models. Root Mean Square Error (RMSE) was used to assess the accuracy of the models with the RMSE of model A is 14.3 cm, model B is 15.7 cm and model C is 14.5 cm, respectively. The inclusion of height term (∆h) in model B does not improve the accuracy over model A and model C. Model A with the lowest RMSE is hence the better of the three models. One-way ANOVA test conducted at 95% confidence level, however, revealed that the three models did not differ significantly. Model A having lower RMSE is recommended with GPS determined ellipsoidal heights as an alternative to conventional spirit levelling for orthometric height determination within Akure for engineering and environmental applications.

New Methodology of Designation the Precise Aircraft Position Based on the RTK GPS Solution.

The paper presents the results of research on improving the accuracy of aircraft positioning using RTK-OTF (Real Time Kinematic–On The Fly) technique in air navigation. The paper shows a new solution of aircraft positioning for the application of the differential RTK-OTF technique in air navigation. In particular, a new mathematical model is presented which makes it possible to determine the resultant position of an aircraft based on the solution for the method of least squares in a stochastic process. The developed method combines in the process of alignment of GPS (Global Positioning System) observations, three independent solutions of the aircraft position in OTF mode for geocentric coordinates XYZ of the aircraft. Measurement weights as a function of the vector length and the mean vector length error, respectively, were used in the calculations. The applied calculation method makes it possible to determine the resultant position of the aircraft with high accuracy: better than 0.039 m with using the measurement weight as a function of the vector length and better than 0.009 m with the measurement weight as a function of the mean error of the vector length, respectively. In relation to the classical RTK-OTF solution as a model of the arithmetic mean, the proposed method makes it possible to increase the accuracy of determination of the aircraft position by 45–46% using the measurement weight as a function of the vector length, and 86–88% using the measurement weight as a function of the mean error of the vector length, respectively. The obtained test results show that the developed method improves to significantly improve the accuracy of the RTK-OTF solution as a method for determining the reference position in air navigation.

Land Subsidence Study Using Geodetic GPS and GAMIT/GLOBK Software (Case Study : Banjarasri Village and Kedungbanteng Village, Tanggulangin District, Sidoarjo Regency)

Floods are one of the natural disasters that always occur in various regions in the Republic of Indonesia. Several flood points were recorded in Banjarasri Village and Kedungbanteng Village, Tanggulangin District, Sidoarjo Regency. There is an allegation that one of the factors causing the flooding in the two villages was caused by land subsidence. Therefore, it is necessary to conduct a study to monitor the magnitude of land subsidence in the area. In this study, the Global Positioning System (GPS) observation method was used. The research was carried out by collecting data from six points which were carried out over three periods of time, namely on 22 - 27 October 2020, 24 - 29 November 2020, and 24 - 29 March 2021. Based on the results of processing and analyzing GPS data, the observed values for shift and motion vectors are obtained. There were five points of land subsidence statistically, which included BM02, BM03, BM04, BM05, and BM06 with values of respectively 3.6 cm, 7.3 cm, 5.9 cm, 4.8 cm, and 5.2 cm. The horizontal position vector moves in various ways, where BM01 and BM04 move to the southwest as far as 2.5 cm and 1.9 cm, BM05 moves to the southeast with a shift of 3.3 cm, and BM06 moves to the northeast with a shift of 4.2 cmFloods are one of the natural disasters that always occur in various regions in the Republic of Indonesia. Several flood points were recorded in Banjarasri Village and Kedungbanteng Village, Tanggulangin District, Sidoarjo Regency. There is an allegation that one of the factors causing the flooding in the two villages was caused by land subsidence. Therefore, it is necessary to conduct a study to monitor the magnitude of land subsidence in the area. In this study, the Global Positioning System (GPS) observation method was used. The research was carried out by collecting data from six points which were carried out over three periods of time, namely on 22 - 27 October 2020, 24 - 29 November 2020, and 24 - 29 March 2021. Based on the results of processing and analyzing GPS data, the observed values for shift and motion vectors are obtained. There were five points of land subsidence statistically, which included BM02, BM03, BM04, BM05, and BM06 with values of respectively 3.6 cm, 7.3 cm, 5.9 cm, 4.8 cm, and 5.2 cm. The horizontal position vector moves in various ways, where BM01 and BM04 move to the southwest as far as 2.5 cm and 1.9 cm, BM05 moves to the southeast with a shift of 3.3 cm, and BM06 moves to the northeast with a shift of 4.2 cm.