Session - Modelling the Earth's ionosphere and solutions to counter ionospheric threats to GNSS applications
Marcio Aquino, Cathryn Mitchell, Giorgiana De Franceschi
The Earth's ionosphere is a complex system that is driven by many different factors such as solar radiation, electric and
magnetic fields, and neutral atmosphere dynamics. New models and data to realise the state of the Earth's ionosphere are
of interest to radio system users whose signals are affected by ionospheric propagation, in particular navigation and
communications systems operating below 3 GHz. Global Navigation Satellites Systems (GNSS), which have become essential
in support of a growing number of activities now embedded in modern society, are especially vulnerable to signal propagation
through the ionosphere. In this context this session addresses models and solutions to mitigate ionospheric threats to GNSS
and related applications. The TRANSMIT project, an FP7 funded Marie Curie Initial Training Network,
has focused on the understanding and development of new models that can be tested for their usefulness in
addressing radio system specification with a view to support the development of concepts and operational tools
that could contribute to a service to assist European users in countering GNSS vulnerability to ionospheric phenomena.
Results of this project are expected to be showcased in this session, as well as any other initiatives in this area.
The session welcomes work in the areas of ionospheric tomography and imaging, radio occultation, scintillation and
interference resilient receiver tracking models and implementations, real time positioning algorithms (e.g. for
Precise Point Positioning) to mitigate ionospheric threats affecting legacy and new GNSS signals, scintillation and
TEC prediction models and operational tools, as well as any other related topics. The main aim of the session is to
stimulate discussion and encourage new collaborative work.
Invited Talks and First Class Posters
Tuesday November 18, 09:00 - 10:50
| 1 |
Oral |
9:00 am |
An Improved Ionospheric Modeling
Technique Using GPS and Empirical-Orthogonal-Function Fits |
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Zhang, W1; Langley, R B1; Komjathy, A2; Banville, S3 |
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1University
of New Brunswick; 2Jet Propulsion Laboratory & University of New Brunswick; 3Natural Resources Canada
& University of New Brunswick |
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The dispersion of the ionosphere
pertaining to Global Positioning System (GPS) signals allows us to gain
information on its morphology in terms of total electron content (TEC) or
electron density along the individual signal ray paths, and the generation of
2D or 3D ionospheric models. Several steps are typically involved in
ionospheric modeling, such as data preprocessing to obtain slant TECs
(STECs), estimating receiver and satellite biases and eliminating them from
the STECs, and fitting the STEC (or converted vertical TEC (VTEC)) values
with a mathematical model. Spherical harmonic functions (SHF), wavelet bases,
and polynomial functions are typically employed in the mathematical model to
depict the horizontal variability of the ionosphere for global and regional
ionospheric modeling. However, while using functions of higher order is a
usual practice for more precise results in terms of lower post-fit residuals,
it may induce model instability, estimated states being unobservable, or a
potential heavy computing burden. This is especially the case for disturbed
ionospheric conditions with irregular “behavior” of the ionosphere. To
overcome any downsides of the function-based models, the Kriging algorithm
was introduced for ionospheric modeling. Its benefit of assigning weights
according to a data-driven weighting function rather than any arbitrary
functions was demonstrated by some related works on the algorithm design for
the Wide Area Augmentation System (WAAS). However, the accuracy of the model
may still be limited by the accuracy of inter-frequency hardware biases
(IHBs), which are typically estimated under some assumptions, such as the
thin shell assumption to convert STECs to VTECs and/or some other
mathematical representation of the ionosphere. In this paper, attempting to
make the estimated parameters more meaningful and effective, we propose an
ionospheric modeling technique that uses data-driven empirical orthogonal
functions (EOFs) to replace arbitrary functions to match the horizontal
variability of the ionosphere and estimate IHBs with the EOF-fit
representation of the ionosphere. We then assess the newly proposed model by
analyzing the post-fit residuals of the estimation process, as well as the
repeatability of estimates of IHBs in both 2D and 3D modeling scenarios. For
the 2D scenario, we use the thin shell mapping function, and for the 3D
scenario, we use EOFs to depict the vertical variability, so that all the
three dimensions in this case are represented by EOFs. |
| 2 |
Oral |
9:15 am |
Ionospheric Data Assimilation |
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Da Dalt, F1; Panicciari, T1; Benton, C1; Smith, N1; Mitchell, C1 |
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1University
of Bath |
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One of the manifestations of
space weather is the high variability of the ionosphere. Signals propagating
through this part of the atmosphere are adversely affected by its presence
and dynamics, particularly the Global Navigation Satellite Systems (GNSS).
The need for a better understanding of the characteristics and behaviour of
this medium resulted in the realization of MIDAS (Multi-Instrument Data
Analysis System). Developed at the University of Bath, MIDAS is a software
package that provides three dimensional reconstructions of ionospheric plasma
density from GPS (Global Positioning System) measurements collected by
ground-based receivers. These measurements, known as Total Electron content
(TEC) and expressed in TECU (TEC units [1016 particles/m2]), are integrated
electron density values along a specific signal path. MIDAS algorithms gather
and utilise various TEC measurements to compute reconstructions of the
ionosphere through tomographic inversion. Unfortunately, the
satellite-receiver path arrangements do not provide an ideal scan geometry
for the reconstructions. Further, the ground receivers do not cover the Earth
surface homogenously. This translates to a poor data coverage and lack of
information that prevents the inversion from having a unique solution. To
overcome this problem, the inversion in MIDAS is supported by regularization
methods and external information provided by empirical models. The presented
project aims to implement a physics-based ionospheric model into MIDAS by
means of a Data Assimilation (DA) scheme. The objective is twofold: obtain
higher accuracy ionospheric reconstructions using physics-based support and
be used as a forecasting tool. To reach the aforementioned goals, A New
Ionospheric Model (ANIMo) was developed and validated at the University of
Bath. ANIMo is a global model – it
solves the continuity equation for monoatomic oxygen O+ in a three
dimensional grid of altitude, latitude and longitude. It performs reconstructions
in an altitude range from 80 to 600 km and is designed to be used in
mid-latitude regions. ANIMo assumes that the sum of the major ions densities
(O+, NO+ and O2+) is equal to the electron density. It was developed to
conform to specific requirements necessary for its final implementation in
MIDAS. The first-principles nature of ANIMo is very relevant not only for
prediction but also to enable better control over the whole assimilative
procedure. This permits the use of the model to test the importance of
different input parameters or to simulate particular ionospheric conditions.
For similar reasons, the model was intentionally developed to exhibit
simplicity and robustness. The application of ANIMo in MIDAS is mainly
performed through a DA approach known as 4D-Var. Largely used in meteorology,
this type of assimilative scheme typically has an iterative nature. Here,
ANIMo provides the background (or a priori) estimates that, combined with the
GPS observations, give the analysis – an image of the true state of the
ionosphere at a given point in space and time. The analysis can be then used
to initialize ANIMo to compute a new analysis at the next time step or to
perform routine forecasting. The model contribution is weighted by the
background covariance matrix. The latter is constructed in this scheme by
considering time-dependent horizontal correlation distances of electron
density. ANIMo is also used to provide a physical constraint in the
reconstructions of vertical profiles, which represents a critical phase when
imaging the ionosphere through tomography. Promising preliminary results
suggest that the presented assimilative scheme is not only able to provide
accurate ionospheric images but also the opportunity for prediction.
Furthermore, this setup could be used as a benchmark to test the importance
of external forcing factors when modelling the upper atmosphere; therefore
useful for the whole ionospheric forecasting community. |
| 3 |
Oral |
9:30 am |
Geomagnetic Control of
Equatorial Plasma Bubble Activity Modeled by the TIEGCM with Kp |
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Carter, B1; Francis, M2; Retterer, J1; Yizengaw, E1; Groves, K1; Caton, R3; McNamara, L3; Bridgewood, C1; Terkildsen, M2; Norman, R4; Zhang, K4 |
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1Institute
for Scientific Research, Boston College; 2IPS Radio and Space Services, Australian Bureau of Meteorology;
3Air Force
Research Laboratory, Kirtland AFB, New Mexico; 4SPACE Research Centre, RMIT University, Melbourne |
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Describing the day-to-day
variability of Equatorial Plasma Bubble (EPB) occurrence has remained a
significant challenge over several decades. The importance in pursuing such a
task has increased significantly in recent years due to the increased use and
reliance upon Global Navigation Satellite Systems for navigation, positioning
and timing. In this study we use the Thermosphere Ionosphere Electrodynamics
General Circulation Model (TIEGCM), driven by solar (F10.7) and geomagnetic
(Kp) activity indices, to study daily variations of the linear
Rayleigh-Taylor (R-T) instability growth rate in relation to the measured
scintillation strength at five longitudinally distributed stations. For
locations characterized by generally favorable conditions for EPB growth
(i.e., within the “scintillation season” for that location) we find that the
TIEGCM is capable of identifying days when EPB development, determined from
the calculated R-T growth rate, is suppressed as a result of geomagnetic
activity. Observed and modeled upward plasma drift indicates that the
pre-reversal enhancement best scales linearly with Kp from ~ 3.5 hrs prior,
from which it is concluded that even small Kp changes cause significant
variations in EPB growth, and the likelihood of associated radio
scintillation events on any given day. |
| 4 |
Oral |
9:45 am |
Zonal Velocity of the Equatorial
Ionospheric Irregularities over São Paulo State, Brazil, during the last
Solar Maximum |
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Cesaroni, C1; Spogli, L1; De Franceschi, G1; Alfonsi, L1; Romano, V1; Aquino, M2; Park, J2; Monico, J F G3 |
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1INGV;
2University
of Nottingham 3UNESP |
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The South American ionosphere is
characterized by the presence of the Equatorial Ionospheric Anomaly (EIA),
which results in two crests of enhanced electron density located at ±15° off
the magnetic equator. Such characterization implies a complex configuration
and dynamics of the local ionospheric plasma, especially during solar maximum
conditions. In the framework of the FP7 project CALIBRA (Countering GNSS high
Accuracy applications LImitations due to ionospheric disturbances in BRAzil)
three dual-frequency multi-constellation GNSS receivers have been installed
in the state of São Paulo, in the region of Presidente Prudente (22°07′32″S,
51°23′20″W), in order to study the dynamics of the irregularities near the
southern crest of the EIA. These receivers (PRU1, PRU2 and PRU3) are located
on the vertices of an equilateral triangle at a distance of about 300 meters
from each other to allow the study of the dynamics of the irregularities of
the dimension of the Fresnel scale for L-band signals. In particular, PRU1
and PRU3 are located along the E-W magnetic direction, while PRU1 and PRU2
along the N-S direction. Following the study carried out by Ledvina (2004),
it is possible to estimate the zonal velocity of the irregularities from the
knowledge of the zonal velocity of the scintillation pattern (vscint) and the
position (xsat) and velocity (vsat) of the satellites. In this paper, we use
a cross-correlation technique, applied to 50 Hz raw-data from the receivers
located in Presidente Prudente, to estimate vscint and the orbital parameters
of the GPS satellites included in the RINEX navigational files to evaluate
xsat and vsat. The present study has been carried out by using data acquired
during a measurement campaign from August 2013 to April 2014, in order to
show the daily variability of the zonal velocity of the irregularities. |
| 5 |
Oral |
10:00 am |
Current
capability of GNSS ionospheric tomography in Antarctica |
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Kinrade, J1; Panicciari, T2; Smith, N2; Mitchell, C2 |
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1IEEA;
2University
of Bath; 2University
of Bath |
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Global Navigation Satellite
System (GNSS) tomography can provide three-dimensional and time dependent
reconstructions of ionospheric electron density, on global and regional
scales. Tomography is particularly useful at high latitudes, where
ionospheric observations can be sparse and unevenly distributed due to the
respective topography and remote environments of the Arctic and Antarctica.
Following expansion of ground receiver networks over the last decade through
various polar campaigns, tomography is now a proven tool for imaging plasma
morphology at Arctic latitudes. Tomographic reconstructions have been
compared and verified with independent instruments, including Incoherent
Scatter Radar (ISR) and in-situ satellites, revealing features such as the
mid-latitude trough [e.g. Mitchell et al., 1997] and moving patch
enhancements [e.g. Bust & Crowley, 2007; Spencer & Mitchell, 2007].
Tomography played a key role in profiling the ionosphere’s northern
hemisphere response during the Halloween 2003 geomagnetic storm [e.g.
Mitchell et al., 2005]. However, there has been historically poor and uneven
data coverage in Antarctica compared with the Arctic. The first tomographic
images of the Antarctic ionosphere were produced using measurements from two
ground stations [Heaton et al., 1996], but even with a distribution of
approximately 50 stations across the continent today, wide-area tomographic
reconstructions over Antarctica [e.g. Yin et al., 2010; Kinrade et al., 2012]
are limited in area extent and feature resolution compared with those in the
northern hemisphere. This work offers a brief review and current status of
ionospheric tomography in Antarctica, and using case studies highlights the
capability of the University of Bath’s Multi Instrument Data Analysis
Software (MIDAS) [Mitchell & Spencer, 2003]. Current work from the Marie
Curie TRANSMIT Initial Training Network (ITN) aims to adapt the MIDAS
algorithm to achieve multi-scale feature resolution in areas of poor data
coverage, an important step towards better detection and tracking of discrete
ionospheric structures in Antarctica.
References BUST, G. S., and G.
Crowley (2007), Tracking of polar cap ionospheric patches using data
assimilation, J. Geophys. Res., 112, A05307, doi:10.1029/2005JA011597.
HEATON, J.A.T., G.O.L. Jones and L. Kersley (1996), Toward ionospheric
tomography in Antarctica: first steps and comparison with dynasonde
observations, Antarctic Science, 8, pp. 297-302,
doi:10.1017/S0954102096000430. KINRADE, J., C. N. Mitchell, P. Yin, N. Smith,
M. J. Jarvis, D. J. Maxfield, M. C. Rose, G. S. Bust, and A. T. Weatherwax
(2012), Ionospheric scintillation over Antarctica during the storm of 5–6
April 2010, J. Geophys. Res., 117, A05304, doi:10.1029/2011JA017073.
MITCHELL, C. N., I. K. Walker, S. E. Pryse, I. Kersley, I. W. McCrea, and T.
B. Jones (1997), First complementary observations by ionospheric tomography,
the EISCAT Svalbard radar and the CUTLASS HF radar, Ann. Geophys., 16(11),
pp. 1519-1522, doi:10.1007/s00585-998-1519-2. MITCHELL, C. N. and P. S. J.
Spencer (2003), A three-dimensional time-dependent algorithm for ionospheric
imaging using GPS, Ann. Geophys., 46(4), pp. 687-696, doi:10.4401/ag-4373.
MITCHELL, C. N., L. Alfonsi, G. De Franceschi, M. Lester, V. Romano, and A.
W. Wernik (2005), GPS TEC and scintillation measurements from the polar
ionosphere during the October 2003 storm, Geophys. Res. Lett., 32(12),
L12S03. SPENCER, P. S. J. and C. N. Mitchell (2007), Imaging of fast moving
electron-density structures in the polar cap, Annals of Geophysics, 50 (3),
pp. 427-434, doi:10.4401/ag-3074. YIN P., C. N. Mitchell, L. Alfonsi, M.
Pinnock, P. Spencer, G. De Franceschi, V. Romano, P. Newell, P. Sarti, M.
Negusini, A. Capra (2009), Imaging of the Antarctic ionosphere: Experimental
results, J. Atmos. and Sol.-Terr. Phys., 71(17-18), pp. 1757-1765,
doi:10.1016/j.jastp.2009.09.014. |
| 1 |
First class poster |
10:20 AM |
Development and Investigation of
Applicability of Parameters Describing Performance of GPS Point Positioning
under the Presence of Ionospheric Anomalies |
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Wezka, K |
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Technische Universität Berlin |
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In a real time GNSS single
receiver based processing mode, such as Precise Point Positioning (PPP),
verification and confirmation of a high trust degree towards the estimated
coordinates is a very critical issue. Especially harmful for those
positioning approaches are random and un-modelled errors which can adversely
affect the GPS signal and degrade accuracy and reliability of navigation
solution. Ionospheric perturbations
described as fast and random variability of plasma density in the ionosphere
are difficult to predict, to detect and to model. Occurrence of some strong
ionospheric disturbances can cause, inter alia, degradation and interruption of GNSS
signals or even lead to loss of signal. Under the presence of ionospheric
disturbances a quality monitoring system of PVT (positioning, velocity and
time) solutions can play a crucial role in enhancing of reliability of data
processing results. In the author's previous
reports two sets of system performance parameters have been proposed.
The first set of the parameters has been selected for data quality control
(QC) of the raw GNSS observations. This set is composed of: number of cycle slips detected, number of
not-correctable cycle slips, number of loss of locks of signal, number of
single epoch gaps, length of connected carrier phase arcs. The second one has
been defined for examination of the quality, robustness and performance of
the navigation solutions and of performance of the processing strategies. To
the second set inclusion of precision and accuracy, integrity, availability,
confidence- and significance level, convergence time to reach the request
accuracy have been suggested. In
consideration of perturbations of GNSS signal propagation one of the most
crucial requirement is an effective Receiver Autonomous Integrity Monitoring
(RAIM) approach suitable to track autonomously consistency of the navigation
signals (measurements). Furthermore, important expectation from RAIM systems
is to provide up-to-date and valid warnings information to the user when the
system’s performance exceeds specified tolerance of quality levels. Various
selected RAIM techniques are applied to the data sets recorded in quiet and
perturbed ionospheric conditions. To improve efficiency of RAIM algorithm, an
external information source on state of the ionosphere has been used to
enhance reliability of the controlling process. Based on this analysis
usability of the proposed approaches has been evaluated and verified. The paper presents selected results of the
applicability investigations of the proposed parameters in order to ensure a
high level of reliability and accuracy of GNSS real- and near-real time
positioning under the presence of strong ionospheric anomalies. The data-sets
from continuously operated GNSS stations located at high- and low latitudes,
where ionospheric disturbances occur more frequently, have been used for the
analysis. |
| 2 |
First class poster |
10:25 AM |
Development Of Ionospheric
Forecast Model Over Malaysia Region |
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Bahari, S A1; abdullah, M1; hasbi, A M1 |
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1Universiti
Kebangsaan Malaysia |
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In the near future, Earth could
be faced with the adverse threat of severe space weather that may
significantly affect satellite operations. The top-down space weather
influence can cause large variations in the ionosphere and penetrate to the
Earth's surface. The study on the ionospheric response to space weather can
serve as an early warning and preventive measure to safeguard and maintain
the accuracy of measurements on board satellites and thereby reduce economic
losses. Since space weather has become more prominent due to the fact that
many countries including Malaysia are moving forward using space-based
instruments, the need to produce high-resolution regional ionosphere models
to support navigation, static and kinematic positioning and space weather
research is essential. This project aims to address the need to better
understand the near equatorial orbit (NEqO) through the flagship program
proposed by the National Space Agency (ANGKASA) under the category of ‘The
Use NEqO Orbit for Scientific and Other Applications’. In this project, an
improved regional model (equatorial model) will be developed based on the
spherical cap harmonic analysis (SCHA) method. This model would be the first
regional ionospheric forecast model in the equatorial region. The SCHA is a
regional modeling technique based on solutions of Laplace’s equation over
constrained cap-like region of the Earth. In this project, the ionospheric
TEC over Malaysia is firstly classified into three ionospheric conditions;
“quiet”, “moderate” and “disturbed” based on existing GPS-TEC data. The
regional model of ionospheric TEC over Malaysia will then be developed. The
regional ionospheric condition over Malaysia based on the developed model
will be produced in near real-time. The output of this project will be highly
beneficial as an early warning system to inform stakeholders and government
agencies such as ANGKASA, ATSB, MINDEF, GNSS users and other NEqO satellite
operators. |
| 3 |
First class poster |
10:30 AM |
Morphology of Shape and Drift of
Ionospheric Irregularities and GPS Scintillation Statistics |
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Stevanović, Đ1; Grzesiak, M2; Materassi, M3; W. Wernik, A2 |
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1Space
Research Centre; 2Space Research Centre, Warsaw; 3Istituto dei Sistemi Complessi, CNR, Sesto Fiorentino, Italy |
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On its way from the satellite to
the receiver, a trans-ionospheric radio signal is distorted by the
ionospheric irregularity that causes signal delay, changes in signal's phase
and amplitude, hence producing a complicated diffraction pattern on the ground.
The variability of the ionospheric drifting irregularity shape and small
scale statistics, reflects the ionospheric behaviour during quiet and storm
events, influencing the signal propagation.
The purpose of this investigation is to infer the characteristics of
the ionospheric irregularities from those of the scintillation diffraction
pattern. Plasma drift velocity and irregularity geometry are studied through
the eigen-analysis of the cross-correlation matrix of gradients of the
scintillation pattern. As far as the scintillation statistics of the GPS
signal is concerned, the study of probability distributions of the signal
fluctuations at different scales provides important information useful in
applications. This study has been
performed on radio signal phase and power recorded by GPS monitors located at
high latitudes at Hornsund, Svalbard and at near equatorial site in Brazil.
Data covers periods before, during and after some major events in 2010-2011.
We validated the estimated properties of ionospheric irregularities using
additional independent measurements. |
| 4 |
First class poster |
10:35 AM |
B-spline Model of Ionospheric
Scintillation |
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Priyadarshi, S1; Wernik, A W1 |
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1Space
Research Centre, Poland |
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Using Dynamic Explorer (DE) 2
satellite in-situ data an empirical climatological model for the Northern
Hemisphere high latitude ionosphere is prepared. This model incorporates with
B-spline functions, solar and geomagnetic indices to reproduce amplitude
scintillation index and other ionospheric parameters like turbulence strength
parameter Cs, spectral index. As input to the model Dynamic Explorer 2
satellite retarding potential analyzer plasma density data was utilized with
IRI ionospheric model and phase screen propagation model. Similar model is
prepared for Hornsund (Svalbard) and Warsaw (Poland) using GPS receiver GSV
4004b data. The model for –high latitude scintillation prepared using in situ
data is compared with the ionospheric scintillation model prepared for the
Hornsund (Svalbard). For studying the change in scintillation behavior when
we move from –mid latitude to - high latitude we have compared the B-spline
model for Warsaw (Poland) and Hornsund (Svalbard). The comparison is made on
the basis of seasonal behavior and the behavior of scintillation index for
different geophysical conditions. The GPS data used in the present model have
been corrected for the elevation angle E dependence of scintillation index
using the power law dependence on cosecant (E) derived by Priyadarshi &
Wernik (2013). |
| 5 |
First class poster |
10:40 AM |
Edge-Preserved Imaging of the
Ionospheric Electron Density |
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Panicciari, T1; Smith, N1; Da Dalt, F1; Mitchell, C1 |
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1University
of Bath |
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The ionosphere is a charged and
dynamic medium. Its interaction with an electromagnetic wave can originate
delay and refraction/diffraction effects. These effects take place at
different locations and are caused by ionospheric structures that occur on multiple
scale sizes. The correct localization and identification of those structures
can significantly improve the study of ionospheric behaviour and its effects
in the electromagnetic wave propagation. The imaging of the ionosphere has
been demonstrated successfully in the last decades by using Computerized
Ionospheric Tomographic (CIT) techniques [1]. CIT allows reconstructing the
ionosphere in terms of electron density, and was formerly proposed by Austen
et al. [2]. Observations are collected by ground-based receivers using Global
Positioning System (GPS) and bring the information of the integrated electron
density along the satellite-receiver path. Geometric limitations, together
with uneven and sparse distribution of observations make CIT problem particularly
difficult to solve. Furthermore, there is a need to accommodate
inconsistencies in observations, e.g. due to representativity errors or
residual dispersive offsets in the observations. Therefore, the problem needs
to be regularized and is more challenging as the structures to be resolved
become smaller, i.e. for high resolution tomography. It is proposed a new
technique for ionospheric tomography based on Total Variation (TV)
regularization. TV techniques can help in preserving important details in the
reconstruction such as edges of ionospheric structures. TV is used in
combination with sparse regularization which uses wavelet decomposition to
promote sparsity in the reconstruction. Sparse regularization is used to
compensate for the non-uniform data coverage and provides the input (initial
solution) for the TV algorithm. TV regularization is expected to improve the
detection and location of sharp gradients, in particular for high resolution
CIT. Sharp gradients may cause disturbances in the signal propagation and
their correct location is an important aspect when a high reliability in the
navigation and communications system service is required. [1] G. S. Bust and
C. N. Mitchell, "History, current state, and future directions of ionospheric
imaging," Reviews of Geophysics, vol. 46, 2008 2008. [2] J. R. Austen,
S. J. Franke, and C. H. Liu, "Ionospheric imaging using computerized
tomography," Radio Science, vol. 23, pp. 299-307, 1988. |
| 6 |
First class poster |
10:45 AM |
Performance Analysis of
Ionosphere Empirical Models for Different Phases of a Solar Cycle |
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Najman, P1; Kos, T1 |
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1University
of Zagreb, Faculty of Electrical Engineering and Computing |
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Ionospheric empirical models
have many uses such as mitigation of ionospheric error for single frequency
GNSS (Global Navigation Satellite System) receivers, estimation of satellite
and receiver inter-frequency biases or Total Electron Content (TEC) calibration
(Jakowski et al, 2011). In all cases, good modelling performance is
desirable. Even though the ionospheric empirical models are widely used, they
show significant degree of inaccuracy, especially during the periods with
high solar activity and geographic areas with complex ionospheric dynamics
(Radicella, 2013). In this study, we
evaluate TEC modelling performance of four different ionospheric empirical
models: IRI2012 (International Reference Ionosphere), Klobuchar, NeQuick2 and
NTCM (Neustrelitz TEC Model). We assume that since each empirical model was
developed using different data, their TEC modelling performance can
significantly differ. In other words, while one model can be the most
accurate under certain conditions, for other conditions some another model
can make the most accurate TEC estimation.
The evaluation of the ionospheric models was done by comparison of
their modelled data with Global Ionospheric Maps (GIMs) provided by Center
for Orbit Determination in Europe (CODE). Each CODE GIM covers are between 180 western to
180 eastern longitude, and 87.5 northern to 87.5 southern latitude with grid
resolution of 5 degrees in longitude and 2.5 degrees in latitude ( 73x71 grid
points). The results were expressed with respect to universal time, month,
and value of solar radio flux index F10.7. The analysis was done for each of
the GIM grid point separately to show which TEC model is the most accurate in
different areas. The comparison was
done for two periods: 2003-2005 and 2010-2012 to see how the results change
for different phases of a solar cycle. In addition, results were compared
with the TOPEX satellite data to test if using models according to our
comparison leads to improvement in overall TEC modelling. References:
N. Jakowski, C. Mayer, M. M. Hoque and V. Wilken . Total electron
content models and their use in ionosphere monitoring. Radio Science, 2011.
46(6). doi: 10.1029/2010RS004620 S. M.
Radicella. Ionosphere Electron Density Models - Present Trend and Validation
Issues, 7th European Conference on Antennas and Propagation, 2013 pp. 3931 |
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