Global Navigation Satellite System Applications Research Articles

Correlator beamforming for multipath mitigation in high‐fidelity GNSS monitoring applications

Safety and security critical global navigation satellite system (GNSS) applications ensure system integrity by performing long-term monitoring to quantify and characterize GNSS signal anomalies. Multipath significantly hinders these high-fidelity signal quality monitoring applications. Besides multipath limiting antennas and sophisticated receiver signal processing, any remaining multipath is currently removed by antenna siting and azimuth/elevation masking. As urban development around airports and monitoring installations continues, these solutions may not suffice and more aggressive but cost-effective mitigation technologies are needed. This article explores the application of correlator beamforming as a potential solution. Unlike traditional multielement beamforming that requires a separate receiver front-end for each antenna element, correlator beamforming time multiplexes the received signals and performs beamforming as part of receiver correlation processing. This article shows that the multipath mitigation performance of correlator beamforming significantly exceeds a geodetic antenna and approaches that of traditional multi-element beamforming. The results presented are relevant for all GNSS monitoring applications.

Geospatial Assessment of Crime and Security in Ido Local Government Area, Oyo State, SouthWest Nigeria

Utilization of Information Technology is required in public safety management in the cities and their suburb such as the present Ido area, Ido local government Ibadan. Geographic Information System (GIS) is an important tool that can be used to locate crime area, and thus allow police to proactively respond to the situations before constituting a problem. This research investigates crime and security in Ido Local Government Area of Oyo State, Southwest Nigeria with the aim of mapping and assessing the area prone to crime, leading causes. The methodology adopted in this research was field surveying methods with the use of Hi-target differential GPS to acquire the spatial coordinate (x, y, z) of crime hotspots/locations and police stations in the study area. The local government consists of five areas namely; Omi-Adio with seven (7) communities, Ologuneru with eight (8) communities, Ido with thirteen (13) communities, Apete with fifteen (15) communities and Apata division with eleven (11) communities. The data acquired through field surveying measurement with the Hi-target differential GPS was processed with Hi-target Geomatics Office (HGO) and Global Navigation Satellite System (GNSS) application software in order to acquire the spatial location x, y, z data of the crime hotspots and police stations. Proximity of police stations to crime hotspots was calculated to know how each of the crime hotspot was distant to the police station. Further processing was done with the use of Quick Bird satellite imagery, ArcGIS 10.2.1 (Arcmap 10.2.1) GIS application software in analyzing the location of crime and also identification of crime patterns. The result from the crime data obtained from the field measurement and police was presented in form of charts and map/plan. Generally from the research, it can be concluded that the major crime types common in the study area. Therefore, the security issues in Ido local government has been dealt with but still requires more attentions by the government and the law enforcement agencies.

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.

GNSS Multipath Error Modeling and Mitigation by Using Sparsity-Promoting Regularization

In high-accuracy global navigation satellite system (GNSS) positioning applications, the multipath is one of the primary error sources because it is hard to parameterize. Being somewhat systematic rather than purely random, the multipath should be viewed more as a signal rather than a noise. On this basis, empirically modeling the multipath is realizable. A new sidereal filtering approach based on sparsity-promoting regularization is proposed to mitigate multipath errors for static short baseline GNSS applications. The key idea of the proposed method emphasizes the use of the $L_{1} $ norm to extract multipaths from noisy carrier phase residuals. Two regularization schemes with the first- and second-order differences are considered. For each scheme, efficient numerical algorithms are developed to find solutions by using the Thomas algorithm and the Cholesky rank-one update algorithm as the core of the iteration for the first- and second-order differences, respectively. Regularization parameters or Lagrange multipliers are optimized by using the bootstrap method. By applying the proposed multipath modeling method, the average improvement ratio of the root-mean-square values of double-difference residuals can reach approximately 66.7% compared with the result without multipath mitigation in the two different datasets. Moreover, positioning precision is improved by approximately 20.8%, 26.3%, and 37.8% in the East, North, and Up directions, respectively. Moreover, the fixed rate of ambiguities is improved by 3.7% on average under the kinematic mode.

GPS Multipath Analysis Using Fresnel Zones.

GNSS (Global Navigation Satellite Systems) multipath has been subject to scientific research for decades and although numerous methods and techniques have already been developed to mitigate this effect, it is still one of the accuracy-limiting factors in many GNSS applications. Since multipath is highly dependent on the individual antenna environment, there is still a need for new methods and further investigations to increase the understanding of this systematic effect. In this paper, the concept of Fresnel zones is applied to two different aspects of multipath. First, Fresnel zones are determined for the line-of-sight transmission between satellite and receiver. By comparing the boundary of the Fresnel zones to an obstruction adaptive elevation mask, potentially diffracted signals can be identified and excluded from the position estimation process. Both the percentage of epochs with fixed ambiguities and the positioning accuracy can be increased by the proposed method. Second, Fresnel zones are used to analyze the multipath induced by a horizontal and spatially-limited reflector. The comparison of simulated and real signal-to-noise (SNR) observations reveals a relationship between the percentage of the overlap of the Fresnel zone and reflector and the occurrence of multipath. It is found that an overlap of 50% is sufficient to induce multipath effects. This is of special interest, since this does not confirm theoretical assumptions of the multipath theory.

New range domain carrier‐smoothed code filtering with dual‐frequency BDS data

AbstractIn global navigation satellite system (GNSS) applications, the carrier‐smoothed code is a widely used technique to combine code pseudo‐range and carrier phase measurements. Unlike conventional methods, a method using dual‐frequency GNSS data to improve smoothing accuracy by eliminating ionosphere delay is described in this paper. In the recursive least‐squares theory for colored measurement errors framework, a global one‐step carrier‐smoothed code filter in range domain is proposed to overcome the limitations of traditional approaches. The correlations of the time‐differenced carrier phase measurements are considered. This approach avoids overly optimistically evaluating the estimate and improves the transient accuracy of the estimate. Compared with stepwise strategy, the one‐step method is superior and globally optimal. Experiments are conducted using real BDS data, and the performance of the proposed method is demonstrated.

A Compact Meandered Ring Antenna Loaded With Parasitic Patches and a Slotted Ground for Global Navigation Satellite Systems

A compact meandered ring patch antenna loaded with four parasitic-grounded patches and a slotted ground is proposed. It has two orthogonal T-shaped coupling line feeds with different lengths which produce circularly polarized radiation. The ground is developed with an inner square patch with four symmetric slant corner cuts and an outer ring that further reduces the overall size of the proposed antenna. The measured frequency band with $\vert S_{11}\vert dB, the axial ratio (AR) band with AR $0.169 \times 0.169\,\,\lambda _{\mathrm {g}}^{2}$ and the overall size of the proposed antenna is $0.285\,\,\lambda _{\mathrm {g}}\times 0.285\,\,\lambda _{\mathrm {g}}\times 0.035\,\,\lambda _{\mathrm {g}}$ ( $\lambda _{\mathrm {g}}$ denotes the guide wavelength at the center frequency). The proposed antenna is smaller than the existing antennas and can be an ideal compact antenna used for global navigation satellite system applications.

Residuals of Tropospheric Delays from GNSS Data and Ray-Tracing as a Potential Indicator of Rain and Clouds

The Global Navigation Satellite System (GNSS) is commonly recognized by its all-weather capability. However, observations depend on atmospheric conditions which requires the induced tropospheric delay to be estimated as an unknown parameter. In the following study, we investigate the impact of intense weather events on GNSS estimates. GNSS slant total delays (STD) in Precise Point Positioning technique (PPP) strategy were calculated for stations in southwest Poland in a 56 days period covering several heavy precipitation cases. The corresponding delays retrieved from Weather Research and Forecasting (WRF) model by a ray-tracing technique considered only gaseous parts of the atmosphere. The discrepancies are correlated with rain rates and cloud type products from remote sensing platforms. Positive correlation is found as well as GNSS estimates tend to be systematically larger than modeled delays. Mean differences mapped to the zenith direction are showed to vary between 10 mm and 30 mm. The magnitude of discrepancies follows the intensity of phenomena, especially for severe weather events. Results suggest that effects induced by commonly neglected liquid and solid water terms in the troposphere modeling should be considered in precise GNSS applications for the atmosphere monitoring. The state-of-art functional model applied in GNSS processing strategies shows certain deficits. Estimated tropospheric delays with gradients and post-fit residuals could be replaced by a loosely constrained solution without loss of quality.

Decoding Performance Analysis of GNSS Messages with Land Mobile Satellite Channel in Urban Environment

Demand for Global Navigation Satellite System (GNSS) applications in the urban environment has experienced a remarkable growth in recent years. However, the received signals are subjected to various urban channel impairments, like shadowing and multipath fading. Therefore, the decoding performance is different from that in open-sky conditions. In this paper, a two-state Land Mobile Satellite (LMS) channel based on the Markov process is used to model the urban channel properties, and then, the analysis of decoding performance in terms of frame error rate (FER) in the LMS channel is performed by evaluating the effect of three major influencing factors, specifically, coding and interleaving in the GNSS message, terminal speed, and satellite elevation angle. Extensive simulations are conducted on BDS-3 B1C B-CNAV1 message and GALILEO E5a F/NAV message. The results validate the excellent error correcting performance of the nonbinary low density parity check (NB-LDPC) code of the B-CNAV1 message and the effectiveness of interleaving in both of the messages in urban condition. Furthermore, it also shows that decoding performance improvement can be achieved with higher terminal speed and higher elevation angle in urban scenarios.

Refinement of global ionospheric coefficients for GNSS applications: Methodology and results

We developed the methodology for the optimal estimation of global ionospheric coefficients of the current Global Navigation Satellite Systems (GNSSs), including the eight- and ten-parameter Klobuchar-like as well as NeQuick models. The ionospheric coefficients of those correction models are calculated from two sets of globally distributed tracking stations of the International GNSS Services (IGS). Performance of the re-estimated Klobuchar-like and NeQuick coefficients are validated during 2002–2014 over the continental and oceanic areas, respectively. Over the continental areas, GPS TECs derived from 40 ground GPS receivers are selected as reference. The eight-, ten-parameter Klobuchar-like and NeQuick models can mitigate the ionospheric delay by 65.8, 67.3 and 75.0%, respectively. Over the global oceans, the independent TECs derived from Jason-1&2 altimeters are used as reference. The re-estimated ionospheric correction models can mitigate 56.1–66.7% of the delay errors. Compared to the original GPS Ionospheric Correction Algorithm (ICA), performance of those eight-, ten-parameter Klobuchar-like and NeQuick models has improved 3.4, 5.9 and 13.4% during the whole test period, respectively. The methodology developed here takes the advantage of high-quality ionospheric TECs derived from the global network of GNSS receivers. The re-estimated ionospheric coefficients can be used as precise ionospheric products to monitor and assess GNSS broadcast ionospheric parameters and to improve the performance of various single-frequency GNSS applications.

On the Mitigation of Ionospheric Scintillation in Advanced GNSS Receivers

Ionospheric scintillation is one of the major threats and most challenging propagation scenarios affecting Global Navigation Satellite Systems (GNSS) and related applications. The fact that this phenomenon causes severe degradations only in equatorial and high latitude regions has led to very few contributions dealing with the fundamental scintillation mitigation problem, being of paramount importance in safety critical applications and advanced integrity receivers. The goal of this paper is twofold, first to bring together the most relevant contributions on GNSS receiver design under scintillation conditions, and then, to propose a new GNSS carrier tracking framework and scintillation mitigation methodology. Scintillation complex gain components are modeled as AR processes and embedded into the state-space formulation, providing the filter the capability to distinguish between dynamics and phase scintillation contributions. In addition, the actual need of robust solutions is solved by using an adaptive filtering approach and directly operating with the baseband received signal. Simulation results, using both synthetic and real scintillation data, are provided to support the theoretical discussion and to show the performance improvements of such new approach.

Special Issue on Application of GNSS for Mitigating Natural Disaster

The Global Navigation Satellite System (GNSS) has been utilized in a variety of research fields within the geosciences. This research has been further developed for application to hazard monitoring and natural disaster mitigation. Some developments have even been implemented in society in countermeasures against natural disasters. The Geospatial Information Authority of Japan (GSI), for example, has established a nationwide GNSS network called GEONET. The data from GEONET are used extensively among researchers and practitioners, not only for basic research but also for the development of methods and systems that can mitigate disasters. This special volume is a collection of articles that discuss how such methods and systems are now being developed and/or planned to both clarify the mechanisms behind natural hazards and mitigate the damage they may cause. The volume consists of 13 papers covering a wide range of natural phenomena, such as earthquakes, crustal movements, tsunamis, ionospheric disturbances, and volcanic eruptions. Some papers help us to understand how natural hazards behave, which should be the first step toward disaster mitigation. On the other hand, other articles report direct efforts made toward providing early warnings of impending disasters. Disaster mitigation systems may require real-time (and even kinematic with high-rate data sampling) processing and dissemination of data. Moreover, some applications involve data collection from coastal waters and the open sea. Now that the density of GNSS stations has approached saturation on land, the scarcity of data collected offshore will have to be rectified through the development of GNSS systems in the ocean. We do hope that this volume will be a step in the further progress of utilizing GNSS for disaster monitoring and mitigation in the future to make society safer and more secure.

The Barcelona ionospheric mapping function (BIMF) and its application to northern mid-latitudes

A simple way of improving the Global Navigation Satellite Systems (GNSS) slant ionospheric correction from Vertical Total Electron Content (VTEC) models is presented. In many GNSS applications, a mapping function is required to convert from VTEC, which may be provided in Global Ionospheric Maps (GIMs), to Slant TEC (STEC). Typical approaches assume a single ionospheric shell with constant height, which is unrealistic, especially for low-elevation signals. To reduce the associated conversion error, we propose the Barcelona Ionospheric Mapping Function and its first implementation at northern mid-latitudes (BIMF-nml). BIMF is based on a climatic prediction of the distribution of the topside vertical electron content fraction of VTEC (hereinafter µ2). BIMF is convenient to be applied since no external data are required in practice. To evaluate its performance, we use as independent reference the STEC difference (so-called dSTEC) values directly measured from mid-latitude dual-frequency Global Positioning System (GPS) receivers that have not been used in the computation of the VTEC GIMs under assessment. It is shown that the use of BIMF improves the GIM STEC estimation compared to the single-layer assumptions. This is the case for the mapping functions used by the International GNSS Service (IGS) and Satellite-Based Augmentation Systems (SBAS). This improvement is valid not only for the UPC GIMs, up to 15% for the year 2014, but especially for the GIMs of other analysis centers, such as those produced by CODE and JPL, up to 32 and 29%, respectively.

Statistical Multipath Model Based on Experimental GNSS Data in Static Urban Canyon Environment.

A deep understanding of multipath characteristics is essential to design signal simulators and receivers in global navigation satellite system applications. As a new constellation is deployed and more applications occur in the urban environment, the statistical multipath models of navigation signal need further study. In this paper, we present statistical distribution models of multipath time delay, multipath power attenuation, and multipath fading frequency based on the experimental data in the urban canyon environment. The raw data of multipath characteristics are obtained by processing real navigation signal to study the statistical distribution. By fitting the statistical data, it shows that the probability distribution of time delay follows a gamma distribution which is related to the waiting time of Poisson distributed events. The fading frequency follows an exponential distribution, and the mean of multipath power attenuation decreases linearly with an increasing time delay. In addition, the detailed statistical characteristics for different elevations and orbits satellites is studied, and the parameters of each distribution are quite different. The research results give useful guidance for navigation simulator and receiver designers.

A Frequency-Domain Multipath Parameter Estimation and Mitigation Method for BOC-Modulated GNSS Signals.

As multipath is one of the dominating error sources for high accuracy Global Navigation Satellite System (GNSS) applications, multipath mitigation approaches are employed to minimize this hazardous error in receivers. Binary offset carrier modulation (BOC), as a modernized signal structure, is adopted to achieve significant enhancement. However, because of its multi-peak autocorrelation function, conventional multipath mitigation techniques for binary phase shift keying (BPSK) signal would not be optimal. Currently, non-parametric and parametric approaches have been studied specifically aiming at multipath mitigation for BOC signals. Non-parametric techniques, such as Code Correlation Reference Waveforms (CCRW), usually have good feasibility with simple structures, but suffer from low universal applicability for different BOC signals. Parametric approaches can thoroughly eliminate multipath error by estimating multipath parameters. The problems with this category are at the high computation complexity and vulnerability to the noise. To tackle the problem, we present a practical parametric multipath estimation method in the frequency domain for BOC signals. The received signal is transferred to the frequency domain to separate out the multipath channel transfer function for multipath parameter estimation. During this process, we take the operations of segmentation and averaging to reduce both noise effect and computational load. The performance of the proposed method is evaluated and compared with the previous work in three scenarios. Results indicate that the proposed averaging-Fast Fourier Transform (averaging-FFT) method achieves good robustness in severe multipath environments with lower computational load for both low-order and high-order BOC signals.

A new multipath mitigation method based on adaptive thresholding wavelet denoising and double reference shift strategy

Multipath disturbance is one of the major error sources in high-accuracy positioning for global navigation satellite system (GNSS). Although various methods based on software and hardware strategies have been developed to mitigate this error, they are still limited by different kinds of factors and the effect is not ideal. After analyzing the existing methods, a new single-difference sidereal filtering method, based on adaptive thresholding wavelet denoising and double reference shift strategy (ATDR), is proposed to mitigate multipath effects for static short-baseline GNSS applications. The key idea of the proposed method is the use of both the adaptive thresholding wavelet denoising to extract an accurate multipath correction model from the reference Day and the double reference shift strategy to mitigate multipath for subsequent Day 2 more accurately and efficiently. By applying the introduced adaptive thresholding method, the average improvement rate of the RMS values of the single-difference residuals can reach about 15.82% compared with the constant thresholding method. Moreover, after applying the proposed ATDR method, the 3D positioning precision is improved by about 37.73% for the single epoch mode with 30 s data sampling rate and about 31.22% for the continuous mode with 1 s high sampling rate compared with the original results. Even compared with the constant thresholding single orbital reference (CTSR) method, the improvement percentage is about 33.94% in single epoch mode and about 25.40% in continuous mode for 3D positioning precision, respectively. In conclusion, the results of the two experiments indicate that the proposed ATDR method performs much better than the CTSR method in mitigating multipath for different sampling rates and different processing modes in the measurement domain for GNSS static short-baseline postprocessing applications.

A procedure for the significance testing of unmodeled errors in GNSS observations

It is a crucial task to establish a precise mathematical model for global navigation satellite system (GNSS) observations in precise positioning. Due to the spatiotemporal complexity of, and limited knowledge on, systematic errors in GNSS observations, some residual systematic errors would inevitably remain even after corrected with empirical model and parameterization. These residual systematic errors are referred to as unmodeled errors. However, most of the existing studies mainly focus on handling the systematic errors that can be properly modeled and then simply ignore the unmodeled errors that may actually exist. To further improve the accuracy and reliability of GNSS applications, such unmodeled errors must be handled especially when they are significant. Therefore, a very first question is how to statistically validate the significance of unmodeled errors. In this research, we will propose a procedure to examine the significance of these unmodeled errors by the combined use of the hypothesis tests. With this testing procedure, three components of unmodeled errors, i.e., the nonstationary signal, stationary signal and white noise, are identified. The procedure is tested by using simulated data and real BeiDou datasets with varying error sources. The results show that the unmodeled errors can be discriminated by our procedure with approximately 90% confidence. The efficiency of the proposed procedure is further reassured by applying the time-domain Allan variance analysis and frequency-domain fast Fourier transform. In summary, the spatiotemporally correlated unmodeled errors are commonly existent in GNSS observations and mainly governed by the residual atmospheric biases and multipath. Their patterns may also be impacted by the receiver.

Evaluation of array antenna systems for global navigation satellite system applications using wave‐field synthesis in an over‐the‐air laboratory

Antenna characterisation is usually performed by antenna pattern measurements in an anechoic chamber. Subsequently, a conducted test, the radiated two-stage or the wireless-cable method can be used for an overall system evaluation considering the measured patterns. In this study, the authors present a method to perform device tests for antenna arrays/smart antennas with and without the need of radiation pattern measurements, and they validate it experimentally. By using over-the-air tests in a virtual electromagnetic environment and wave-field synthesis, the propagation environment can be realistically recreated in the region around a device-under-test. This allows for reproducible performance comparisons of different antennas or systems under identical propagation environment conditions. As a special application, they consider the controlled reception pattern antenna in a global navigation satellite systems environment in the presence of interferer signals.

Producing Coordinate Time Series for Iraq's CORS Site for Detection Geophysical Phenomena

Global Navigation Satellite Systems (GNSS) have become an integral part of wide range of applications. One of these applications of GNSS is implementation of the cellular phone to locate the position of users and this technology has been employed in social media applications. Moreover, GNSS have been effectively employed in transportation, GIS, mobile satellite communications, and etc. On the other hand, the geomatics sciences use the GNSS for many practical and scientific applications such as surveying and mapping and monitoring, etc.
 In this study, the GNSS raw data of ISER CORS, which is located in the North of Iraq, are processed and analyzed to build up coordinate time series for the purpose of detection the Arabian tectonic plate motion over seven years and a half. Such coordinates time series have been produced very efficiently using GNSS Precise Point Positioning (PPP). The daily PPP results were processed, analyzed, and presented as coordinate time series using GPS Interactive Time Series Analysis. Furthermore, MATLAB (V.2013a) is used in this study to computerize GITSA with Graphic User Interface (GUI).
 The objective of this study was to investigate both of the homogeneity and consistency of the Iraq CORSs GNSS raw data for detection any geophysical changes over long period of time. Additionally, this study aims to employ free online PPP services, such as CSRS_PPP software, for processing GNSS raw data for generation GNSS coordinate time series.
 The coordinate time series of ISER station showed a +20.9 mm per year, +27.2 mm per year, and -11.3 mm per year in the East, North, and up-down components, respectively. These findings showed a remarkable similarity with those obtained by long-term monitoring of Earth's crust deformation and movement based on global studies and this highlights the importance of using GNSS for monitoring the movement of tectonic plate motion based on CORS and online GNSS data processing services over long period of time.

A new electron density model of the plasmasphere for operational applications and services

The Earth's plasmasphere contributes essentially to total electron content (TEC) measurements from ground or satellite platforms. Furthermore, as an integral part of space weather, associated plasmaspheric phenomena must be addressed in conjunction with ionosphere weather monitoring by operational space weather services. For supporting space weather services and mitigation of propagation errors in Global Navigation Satellite Systems (GNSS) applications we have developed the empirical Neustrelitz plasmasphere model (NPSM). The model consists of an upper L shell dependent part and a lower altitude dependent part, both described by specific exponential decays. Here the McIllwain parameter L defines the geomagnetic field lines in a centered dipole model for the geomagnetic field. The coefficients of the developed approaches are successfully fitted to numerous electron density data derived from dual frequency GPS measurements on-board the CHAMP satellite mission from 2000 to 2005. The data are utilized for fitting up to the L shell L = 3 because a previous validation has shown a good agreement with IMAGE/RPI measurements up to this value. Using the solar radio flux index F10.7 as the only external parameter, the operation of the model is robust, with 40 coefficients fast and sufficiently accurate to be used as a background model for estimating TEC or electron density profiles in near real time GNSS applications and services. In addition to this, the model approach is sensitive to ionospheric coupling resulting in anomalies such as the Nighttime Winter Anomaly and the related Mid-Summer Nighttime Anomaly and even shows a slight plasmasphere compression of the dayside plasmasphere due to solar wind pressure. Modelled electron density and TEC values agree with estimates reported in the literature in similar cases.