Дисертації з теми "Ionosphere Estimation"

This dissertation presents a data assimilation method for estimating the physical drivers of the Earth's ionosphere layer through the combination of Global Navigation Satellite System based (GNSS) ionospheric density measurements, Fabry-Perot interferometer (FPI) neutral wind measurements and several empirical models. The main contributions include: 1) Kalman filtering for multi-observation ingestion and multi-state estimation, 2) ingestion of FPI neutral wind measurements, 3) spherical harmonic basis functions for global electric potential estimation and 4) a study of storm-time ion drifts using globally ingested data.

The thermosphere is a region of Earth's atmosphere (80-1000 km) that contains a balance of particle density and solar ionizing radiation such that an ionosphere can form. During geomagnetic storm events, the ionosphere can be disturbed causing abrupt redistribution of the ionospheric plasma. These disruptions can cause blackouts for radio wave-based communications and navigation systems. Understanding what causes the ionosphere to change is therefore necessary as society becomes more dependent on navigation and communication technologies.

The first step in understanding the ionosphere is to quantify its physical drivers. Measurements of the ionosphere are limited both spatially and temporally because the region is so vast. Models, on the other hand, provide our best understanding and capability to simulate the ionosphere and its drivers but often fall short in capturing certain phenomena during severe geomagnetic storms. In this work, a data assimilation algorithm called Estimating Model Parameters from Ionospheric Reverse Engineering (EMPIRE) is further developed to combine both measurements and simulation data sets for estimating ionospheric drivers globally. EMPIRE ingests ionosphere plasma density rate measurements and subtracts model simulation results to produce an observation of the difference between measurements and simulation. EMPIRE then fits basis functions which represent physical drivers to the measurement-simulation discrepancy. The mapping from observation to physical driver happens using the ion continuity governing equation as a model.

The EMPIRE algorithm was originally developed in 2009 to perform regional data assimilation and used only plasma density measurements. In this work, EMPIRE is modified to use a Kalman filter so measurements and models can be ingested in an efficient and systematic manner. Direct physical driver measurements are provided by FPI neutral wind measurements using the newly developed Kalman filter. This thesis demonstrates the first ever use of FPIs and plasma density measurements in a data assimilative environment. Next, EMPIRE is modified to estimate coefficients to spherical harmonic basis functions rather than power series basis functions. Spherical harmonic functions allow EMPIRE to provide global estimates because they are continuous and orthogonal on a spherical domain (such as Earth). A study is then conducted to ingest global plasma density rate measurements and neutral winds to estimate ion drifts across the globe.

The 2017 Great American Eclipse provided an excellent opportunity for scientists and engineers to study the ionosphere. The dynamics of the ionosphere are affected by the amount of solar radiation it receives and a total solar eclipse produces a short perturbation to the incoming solar radiation. Analyzing how the ionosphere reacts to this type perturbation could lead to new levels of understanding of it. This study develops a nonlinear filter that estimates the state of the ionosphere's 3-D electron density profile given total electron content (TEC) measurements from dual-frequency GPS receivers located on the ground and on low-Earth-orbiting spacecraft. The electron density profile is parameterized by a bi-quintic latitude/longitude spline of Chapman Profile parameters that define the vertical electron density profile. These Chapman parameters and various latitude and longitude partial derivatives are defined at a set of latitude/longitude spline grid points. Bi-quintic interpolation between the points defines the parameters' values and the corresponding Chapman profiles at all latitude/longitude points. The Chapman parameter values and their partial derivatives at the latitude/longitude spline nodes constitute the unknowns that the nonlinear filter estimates. The filter is tested with non-eclipse datasets to determine its reliability. It performs well but does not estimate the biases of the receivers as precisely as desired. Many attempts to improve the filter's bias estimation ability are presented and tried. Eclipse datasets are input to the filter and analyzed. The filter produced results that suggest that the altitude of peak electron density increased significantly near and within the eclipse path and that the vertical TEC (VTEC) was drastically decreased near and within the eclipse path. The changes in VTEC and altitudes of peak electron density caused by the eclipse leave a lasting effect that alters the density profile for anywhere from 15 minutes to several hours.
MS
The 2017 Great American Eclipse garnered much attention in the media and scientific community. Solar eclipses provide unique opportunities to observe the ionosphere’s behavior as a result of irregular solar radiation patterns. Many devices are used to measure this behavior, including GPS receivers. Typically, GPS receivers are used to navigate by extracting and combining carrier phase and pseudorange data from signals of at least four GPS satellites. When the position of a GPS receiver is well-known, information about the portion of the ionosphere that the signal traveled through can be estimated from the GPS signals. This estimation procedure has been done with ground-based and orbiting GPS receivers. However, fusing the two data sources has never been done and will be a primary focus of this study. After demonstrating the performance of the estimation algorithm, it is used to estimate the state of the ionosphere as it was perturbed by the 2017 Great American Eclipse.

This thesis covers two main areas which are related to the mapping and examination of the ionosphere. The first examines the performance and specific nuances of various state-of-the-art interpolation methods with specific application to mapping the ionosphere. This work forms the most widely scoped examination of interpolation technique for ionospheric imaging to date, and includes the introduction of normalised convolution techniques to geophysical data. In this study, adaptive-normalised convolution was found to perform well in ionospheric electron content mapping, and the popular technique, kriging was found to have problems which limit its usefulness. The second, is the development and examination of automatic data-driven motion estimation methods for use on ionospheric electron content data. Particular emphasis is given to storm events, during which characteristic shapes appear and move across the North Pole. This is a particular challenge, as images covering this region tend to have a very-low resolution. Several motion estimation methods are developed and applied to such data, including methods based on optical flow, correlation and boundarycorrespondence. Correlation and relaxation labelling based methods are found to perform reasonably, and boundary based methods based on shape-context matching are found to perform well, when coupled with a regularisation stage. Overall, the techniques examined and developed here will help advance the process of examining the features and morphology of the ionosphere, both during storms and quiet times.

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CNPq
Umas das maiores fontes causadoras de erro no posicionamento GNSS é a ionosfera, sendo que o efeito provocado por esta camada da atmosfera é um dos mais impactantes no processo de estimativa das coordenadas, principalmente para dados coletados com receptores de simples frequência. A modelagem matemática da refração ionosférica é complexa devido às variações diárias, sazonais, de curto e longo período, além de outros fenômenos que ocorrem na atmosfera, tal como a cintilação ionosférica. Em se tratando de posicionamento absoluto com receptores de simples frequência, seja Posicionamento por Ponto Simples (PP) ou Posicionamento por Ponto Preciso (PPP), estratégia adequada de correção dos efeitos ionosféricos devem ser adotadas. A correção da ionosfera para dados de simples frequência pode ser realizada a partir de modelo matemático, tal como o de Klobuchar, Mapas Globais ou Regionais da Ionosfera ou a partir da estimativa residual da ionosfera. Quando se tem disponível dados de duas frequências é possível utilizar a combinação ion-free, a qual permite eliminar os efeitos de primeira ordem da ionosfera. Contudo esta combinação faz com que as ambiguidades percam suas características de números inteiros, bem como realça outros níveis de ruído tal como o multicaminho. Uma possibilidade para atenuar os efeitos da ionosfera é a aplicação da estimativa dos efeitos residuais junto com as coordenadas incógnitas da estação e outros parâmetros. Neste caso, os efeitos da ionosfera podem ser tratados como um processo estocástico no Filtro de Kalman e se pode aplicar tal estratégia para dados de simples ou dupla frequência. Essa estratégia pode facilitar a solução das ambiguidades como inteiras e consequentemente permite a obtenção de resultados mais acurados no posicionamento geodésico. Dentro deste contexto, esta dissertação de mestrado apresenta a avaliação da acurácia do posicionamento absoluto GPS com aplicação de diferentes estratégias de correção da ionosfera. Foram realizados processamentos no modo PPP com dados GPS coletados em estações da RBMC em períodos de alta e baixa atividade solar para os anos de 2010 a 2013, onde se aplicou a correção da ionosfera advinda do modelo de Klobuchar, dos mapas globais (GIM – Global Ionospheric Map) e regionais (LPIM – La Plata Ionospheric Model), além da estimativa residual da ionosfera. As coordenadas estimadas foram comparadas com aquelas advindas da solução semanal SIRGAS-CON, a qual é dada atualmente em ITRF2008 e o Erro Médio Quadrático (EMQ), seja diário ou anual foi utilizado como medidor de acurácia. Ao aplicar as correções da ionosfera advinda dos mapas globais e regionais na estimativa de coordenadas no PPP utilizando somente medidas de código, observou-se melhoria de até 80% em relação ao PPP sem correção da ionosfera. O PPP com correção ionosférica advinda dos mapas regionais produziu melhorias diárias da ordem de 10% em relação ao uso dos mapas globais. Com base nas melhorias produzidas com a utilização do modelo ionosférico regional, foi proposta a modificação do modelo estocástico do ajustamento tendo em vista que somente o modelo funcional é afetado pelas correções ionosféricas advindas dos mapas. Com relação à estimativa residual da ionosfera foram realizados experimentos envolvendo medidas de código e fase na frequência L1 com geração de séries temporais anuais de coordenadas para diversas estações da RBMC, cuja acurácia alcançada foi da ordem de 10 cm no PPP com solução diária.
One of the largest sources of errors in the GNSS positioning is the ionosphere considering that the effect caused by that atmosphere layer is one of the most impacting in the coordinate estimation process, especially for data collected with single frequency receivers. Mathematical modeling of ionospheric refraction is complex due to daily variation in as well as, seasonal short and long period and also other phenomena occurring in the atmosphere such as ionospheric scintillation. Concerning the absolute positioning with single frequency receivers, whether Single Point Positioning (PP) or by Precise Point Positioning (PPP), appropriate strategy to correct the ionospheric effects should be adopted. The ionosphere correction for single frequency data can be performed from mathematical model, such as Klobuchar, Global or Regional Ionosphere maps or from residual ionosphere estimating. When one has available data from two frequencies it is possible to apply the ionosphere free combination which allows eliminating the first order ionosphere effects. However, this combination makes ambiguities lose its integer characteristics as well as amplify other noise levels as for instance multipath. One possibility to mitigate the ionosphere effects is the application of the ionosphere residual estimation along with coordinates station and other parameters. In this case, the ionosphere effects can be treated as a stochastic process in the Kalman filter where it is possible to apply that strategy for single or dual frequency data. This strategy can facilitate the integer ambiguities resolutions and consequently allows obtaining more accurate results in geodetic positioning. Inside this context, this master thesis presents the accuracy evaluation of the GPS absolute positioning by applying different strategies for ionosphere corrections. Processing was performed in PPP mode with GPS data collected in brazilizan RBMC stations in periods of high and low solar activities for the years 2010-2013, where it was applied ionosphere correction from Klobuchar model, global (GIM - Global Ionospheric Map) and regional (LPIM - La Plata Ionospheric Model) maps and the residual ionosphere estimation. The estimated coordinates were compared with those coming from SIRGAS-CON in a weekly solution which is currently given in ITRF2008 and Root Mean Square (RMS), either daily or annually, was used as accuracy measuring. When applying ionosphere corrections from global and regional maps in the PPP coordinates estimation using only code measurements, it was observed improvements of up to 80% comparing with PPP without ionosphere correction. The PPP with ionospheric correction coming from regional maps produced daily improvements of around 10% in relation to applying global maps. Based on improvements reached with corrections from regional ionospheric model, it was proposed the modification of the stochastic model for adjustment considering that only the functional model is affected by the ionospheric corrections coming from maps. Regarding the residual ionosphere estimation experiments were performed involving code and phase measurements in the L1 frequency with generation of coordinates annual time series considering the chosen RBMC stations whose accuracy achieve approximately 10 cm in PPP with daily solution.

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 2007.
Cataloged from PDF version of thesis.
Includes bibliographical references (p. 237-238).
There are many sources of range error in a Global Positioning Satellite (GPS) signal that has traveled to a receiver near the earth's surface. Among these is the ionospheric group delay. In the past, a single-state, dual-frequency filter has been used to estimate the ionospheric delay for authorized users. Although sufficient for terrestrial receivers for which the ionospheric delay changes very slowly, such a filter is inadequate for space-based missions in which a receiver passes rapidly through the ionosphere. Various Kalman filters are examined and simulation results presented. The most robust Kalman filter considered was a seven-state filter. This filter utilizes four measurements: dual-frequency pseudo-range differencing, dual-frequency delta-range differencing, and single-frequency rate measurements for both frequencies (LI and L2). Two states are necessary for the model dynamics plus five constant states necessary for processing rate measurements. The process model selected for the seven-state filter was the integral of a first-order Markov process. The filter was used to estimate both the ionospheric group delay and the deviation of the delay from a given reference model. When used to estimate the deviation of the delay from a reference model, the group delay transitioned from "estimated" to "modeled" smoothly in the absence of measurements. In the absence of measurements, the estimated group delay tends to a bias from the reference model provided.
by Andrea Marie Johnson.
S.M.

Retarding Potential Analyzers (RPA) have a rich flight heritage. These instruments are largely popular since a single current-voltage (I-V) profile can provide in-situ measurements of ion temperature, velocity and composition. The estimation of parameters from an RPA I-V curve is affected by grid geometries and non-ideal biasing which have been studied in the past. In this dissertation, we explore the uncertainties associated with estimated ion parameters from an RPA in the presence of instrument noise. Simulated noisy I-V curves representative of those expected from a mid-inclination low Earth orbit are fitted with standard curve fitting techniques to reveal the degree of uncertainty and inter-dependence between expected errors, with varying levels of additive noise. The main motive is to provide experimenters working with RPA data with a measure of error scalable for different geometries. In subsequent work, we develop a statistics based bootstrap technique designed to mitigate the large inter-dependency between spacecraft potential and ion velocity errors, which were seen to be highly correlated when estimated using a standard algorithm. The new algorithm - BATFORD, acronym for "Bootstrap-based Algorithm with Two-stage Fit for Orbital RPA Data analysis" - was applied to a simulated dataset treated with noise from a laboratory calibration based realistic noise model, and also tested on real in-flight data from the C/NOFS mission. BATFORD outperforms a traditional algorithm in simulation and also provides realistic in-situ estimates from a section of a C/NOFS orbit when the satellite passed through a plasma bubble. The low signal-to-noise ratios (SNR) of measured I-Vs in these bubbles make autonomous parameter estimation notoriously difficult. We thus propose a method for robust autonomous analysis of RPA data that is reliable in low SNR environments, and is applicable for all RPA designs.
Doctor of Philosophy
The plasma environment in Earth’s upper atmosphere is dynamic and diverse. Of particular interest is the ionosphere - a region of dense ionized gases that directly affects the variability in weather in space and the communication of radio wave signals across Earth. Retarding potential analyzers (RPA) are instruments that can directly measure the characteristics of this environment in flight. With the growing popularity of small satellites, these probes need to be studied in greater detail to exploit their ability to understand how ions - the positively charged particles- behave in this region. In this dissertation, we aim to understand how the RPA measurements, obtained as current-voltage relationships, are affected by electronic noise. We propose a methodology to understand the associated uncertainties in the estimated parameters through a simulation study. The results show that a statistics based algorithm can help to interpret RPA data in the presence of noise, and can make autonomous, robust and more accurate measurements compared to a traditional non-linear curve-fitting routine. The dissertation presents the challenges in analyzing RPA data that is affected by noise and proposes a new method to better interpret measurements in the ionosphere that can enable further scientific progress in the space physics community.

The ionosphere, extending from 50 km to 1,000 km above the Earth's surface, is a region of free electrons that cause errors in the measurements of Global Positioning System (GPS) signals. For GPS static studies the ionospheric delay can either be modelled or recovered from dual frequency receivers. However, for real-time kinematic GPS the ionosphere is a major obstacle to carrier phase ambiguity resolution over long baselines with possible aliasing between vertical motion and the ionospheric delay. Several researchers have demonstrated that regional tomographic models of the ionosphere can be constructed from a network of static GPS receivers for implementation in kinematic processing. The purpose of this research is to create mathematically a layered ionospheric tomographic model and analyse a three dimensional (3D) one layer ionospheric tomographic model, voxel-based, for the ionosphere based on GPS data observed from dual-frequency GPS tracking stations, using the carrier phase as the principal observable. This model is fully integrated within Kalman filtering that combines all the parameters and updates the corrections at each epoch. The tomographic model observation equations utilise the two carrier phases (L1and L2 ) directly to estimate the ionospheric parameters. The model thus differs from others that typically use a linear combination of L1and L2 • The model will be used for GPS kinematic processing for long baselines to provide an accurate estimation of the electron density with the purpose of obtaining optimal accuracy of the slant delays due to the ionosphere. A double difference method has been implemented in order to perform the ionospheric measurements and to eliminate possible satellite and receiver dependent biases. The Massachusetts Institute of Technology (MIT) kinematic program, TRACK, has been modified to implement the proposed ionospheric tomographic model. The tomographic ionospheric model has been validated using several days of data from North American GPS stations over an area from about 3t'N to 36'N in Latitude and from 242'E to 246'E in Longitude, forming baselines ranging from 230 km to 400 km. The performance of the estimated ionosphere model has been validated against the United States-Total Electron Content (US-TEC) model. RMS comparisons ranged from 1 TECU (Total Electron Content Unit) to 3 TECU. A comparison of the derived ionosphere maps by using the current US-TEC with the corresponding results extracted using the US-TEC of the preceding day, shows a maximum of 1 TECU difference between maps at hourly intervals, a maximum rms differences of less than 0.5 TECU and a maximum formal uncertainty of less than 1.2 TECU over the area of study. The tests also indicated that the ionospheric tomographic model is robust with enhanced capability comparable to the ionospheric free linear combination (Lc) solutions in terms of GPS phase residuals and ambiguity resolution. On utilising the ionospheric tomographic model the phase residuals rms are typically 4 mm compared with 11 mm on using Lc, while the ambiguity resolution increases to about 84% compared with 78% with Lc. In addition, the average difference between the tropospheric results of the ionospheric tomographic model and Lc is about 10 mm.

International Telemetering Conference Proceedings / October 26-29, 1992 / Town and Country Hotel and Convention Center, San Diego, California
An improved ionospheric delay correction model for a transionospheric electromagnetic pulse (EMP) is used for estimating the total-electron-content (TEC) profile of the path and accurate ranging of the EMP source. For a known pair of time of arrival (TOA) measurements at two frequency channels, the ionospheric TEC information is estimated using a simple numerical technique. This TEC information is then used for computing ionospheric group delay and pulse broadening effect correction to determine the free space range. The model prediction is compared with the experimental test results. The study results show that the model predictions are in good agreement with the test results.

The research of this paper-based dissertation is focused on Global Ionospheric Maps (GIM) generation and assessment. In summary, the novelty and thematic unity in this works relies on four different but complementary topics: 1. Defining a systematic procedure to validate and quantify the quality of GIMs based on independent data sources or techniques. 2. Applying this methodology to not only the GIMs computed at UPC, but also to most of the currently open accessible GIMs inside the scientific community. 3.Including newly available Global Navigation Satellite Systems (GNSS) data to the processing of UPC's GIMs. 4. Assessment and distribution also of real-time GIMs. More in detail, my first contribution has been to the definition of a complete GIM validation procedure. This procedure is based on two methods: direct VTEC (Vertical Total Electron Content) altimeter and GNSS difference of slant TEC (Total Electron Content), both of them giving complementary information of the GIM performance. The main advantage of using satellite altimeter data is the fact that we are using a truly independent information source with regard to the input data used for GIM generation. This allows assessing the TEC from a entirely different point-of-view, fully different and independent to any error that may affect GNSS systems and its processing. The second technique, relies on using the same type of input data but in this case from permanent GNSS stations not participating in the GIM generation. The main advantages of this second technique is twofold: first, it allows to asses the GIMs on land; and second its a low latency direct assessment of the GIM, given a more direct information about the processing and interpolation done with the GNSS input data. Afterwards, a second contribution has been to use the previously defined methodology to validate all the GIMs generated by the International GNSS Service (IGS) Associated Analysis Centers (IAAC), and some other candidates to join them, for a more than a full solar cycle (starting from end of 2001 to beginning of 2017). As a side result, it is also demonstrated that while the time interval of the GIM has little influence on its overall quality, the interpolation technique used by the IAACs has an important role. Finally, this work also lead to the acceptance of the previously mentioned IAAC candidates since it demonstrated the good quality of their GIMs. Another contribution has been, as part of the European GRC project, improving the currently in production UPC's TOMION (TOMographic IONospheric) software used to generate the UQRG (UPC's rapid GIM) map. The software input source data was restricted to GPS L1 and L2. Now it allows processing all current frequencies available for GPS, Galileo and Beidou. This software has been internally tested for some specific days with the previously explained altimeter method giving results with improved quality for specific combinations of GNSS systems and frequencies. Using this work flow but focused on single frequency processing, a last article was published analysing the ionospheric footprint of the solar eclipse over North America during 2017. Finally, another contribution has been to improve the data acquisition and distribution system for the real-time GIM generation processing chain. Furthermore, as part of UPC contribution to the Real Time Ionospheric Monitoring Working Group (RTIM-WG) of the International Association of Geodesy (IAG) and following the previously explained methodology, an assessment of the GIMs generated by the members of this sub-commission have been performed. As a result of all these efforts, UPC has been leading inside the IGS frame, and made a first implementation, of a new real-time combined map.
La recerca realitzada en aquesta tesis en format compendi d’articles esta enfocada en la generació i validació de mapes ionosfèrics globals (GIM, del angles Global Ionospheric Maps). En resum, la novetat i unitat temàtica d’aquesta tesis esta basada en quatre temes diferents però complementaris: • Definició d’un procediment sistemàtic per validar i quantificar la qualitat dels GIMs basada en fonts de dades o tècniques independents. • Aplicar aquesta metodologia no nomes als GIMs generats a UPC, sinó també a la resta de GIMs d’accés obert actualment existent dintre la comunitat científica internacional. • Incloure en el processat per generar els GIMs de UPC dades de les noves constel·lacions GNSS (del angles Global Navigation Satellite Systems) disponibles. • Validació i distribució també dels GIMs en temps real. Com a conseqüència, també s’ha aconseguit generar un primer GIM combinat en temps real. Mes en detall, la meva primera contribució va ser definir un procediment complet de validació de GIM. Aquest procediment esta basat en dos mètodes: obtenció directa del contingut vertical total d’electrons (VTEC, del angles, Vertical Total Electron Content) a partir de dades d’altimetria i per diferencies del contingut total d’electrons (TEC, del angles Total Electron Content) inclinat de dades GNSS. Els dos donen informació complementaria de la qualitat dels GIM. L’avantatge principal d’utilitzar dades de satèl·lits altimètrics es que es una font de dades completament diferent de les que s’utilitzen per la generació dels GIMs. Aquest fet ens permet verificar el TEC des d’una perspectiva diferent, plenament independent de qualsevol font d’error que pugui afectar al propi sistema GNSS o el seu processat. El segon mètode, es basa en la mateix tipus de dades que s’utilitzen pel càlcul dels GIM però en aquest cas amb dades d’estacions permanent GNSS no involucrades en la generació dels GIMs a avaluar. L’avantatge principal d’aquest segon mètodes es doble: primer, permet avaluar el GIM sobre els continents; i segon, permet fer la anàlisis directa de baixa latència del GIM, a mes a mes donant informació directa sobre el processat i la interpolació aplicada sobre les dades GNSS. Seguidament, la meva segona contribució va ser utilitzar la metodologia prèviament definida per validar tots els GIM generats per part dels centres d’anàlisis associats al Servei Internacional de GNSS (IGS, del angles International GNSS Service) i altres centres candidats a unir-se a IGS, per mes d’un cicle solar (des de finals del 2001 fins al inici del 2017). Com a resultat secundari, també va permetre demostrar que per una banda l’interval temporal dels GIM te poca influencia sobre la seva qualitat global, però per altra banda la tècnica d’interpolació emprada per part dels centres te un impacte molt important. Finalment, aquest article va portar a l’admissió d’aquests candidats prèviament mencionats a centres d’anàlisis associats a IGS donat que es va demostrar la bona qualitat dels seus GIMs. Una altra contribució important va ser, com a part del projecte europeu GRC, millorar el software TOMION (TOMographic IONospheric) de UPC, actualment en producció generant el GIM UQRG (GIM ràpid de UPC). Aquest software nomes permetia utilitzar dades de GPS L1 i L2. Les millores realitzades durant aquesta tesis permeten processar totes les freqüències actualment existent de GPS, Galileo i Beidou. El software ha estat internament validat per certs dies específics amb el mètode explicat prèviament d’altimetria millorant els resultats en comparació a la versió anterior per certes combinacions de constel·lacions GNSS i freqüències. Utilitzant aquesta nova metodologia de processat aplicada a una sola freqüència, un últim article va ser publicat analitzant l’empremta ionosfèrica de l’eclipsi solar sobre Amèrica del nord durant el 2017. Finalment, una altre contribució va ser millorar el mètode d’adquisició i distribució del sistema de processat del GIM en temps real. Es mes, com a part de la contribució de la UPC, es va realitzar una validació dels GIMs generats pels participants del grup de treball de monitorització en temps real de la ionosfera (RTIM-WG, del angles Real Time Ionospheric Monitoring Working Group) de l’Associació Internacional de Geodèsia (IAG, del angles International Association of Geodesy) seguint la metodologia anteriorment citada. Com a resultat d’aquestes tasques la UPC ha liderat i mplementat un nou mapa combinat en temps real, en el marc de IGS.

La précision des radars transhorizon dans la localisation des cibles peut être améliorée si le canal de propagation, l'ionosphère, est bien connu. Deux nouvelles méthodes d'inversion capables d'obtenir le profil de densité électronique de l'ionosphère à partir d'ionogrammes de rétrodiffusion sont présentées dans ce manuscrit. Les méthodes utilisent les mesures réalisées par le radar pendant des sondages en élévation. Le problème avec ces données réelles est la présence de beaucoup de points aberrants et l'absence de données pour des angles d'élévation hauts et bas. Les méthodes présentées ici essayent de surmonter ces difficultés et ont été optimisées afin d'être utilisables en temps réel par le radar. A la fin, l'inversion fournit les paramètres d'une ionosphère équivalente qui peut être utilisée pour caractériser la propagation et pour convertir la distance de groupe en distance au sol
Accuracy in target location by over-the-horizon radar (OTHR) can be improved when the propagation channel, the ionosphere, is known. Two inversion methods able to provide an electron density profile of the ionosphere from backscatter ionograms are presented in this document. These methods use the measurements realized by the radar during elevation scans. One difficulty when using measured data is the presence of outliers and, moreover, the lack of data for low elevation and for high elevation angle. The methods presented here tries to overcome these difficulties. At the end, the inversion provides parameters of an equivalent ionosphere that can be used to characterize the propagation and to convert group path into ground range

The ionospheric total electron content (TEC) is the integrated electron density across a unit area. TEC is an important property of the ionosphere. Accurate estimation of TEC and TEC spatial distributions are needed for many space-based applications such as precise positioning, navigation, and timing. The Global Positioning System (GPS) provides one of the most versatile methods for measuring the ionosphere TEC, as it has global coverage, high temporal resolution, and relatively high spatial resolution. The objective of this thesis is to develop an algorithm for accurate estimation of the TEC using dual-frequency GPS receiver measurements and simultaneously estimate the receiver hardware bias in order to mitigate its effect on the TEC. This method assumes the TEC in the portion of sky visible to the receiver can be represented as a two dimensional sheet with an absolute value and spacial gradients with respect to latitude and longitude. A code-phase multipath noise estimation algorithm is integrated with the TEC estimation process to mitigate environmental multipath contamination of the measurements. The integrated algorithm produces an approximate map of local TEC using a single dual-frequency receiver while minimizing both multipath induced errors and the receiver hardware bias. The goal of this method is to provide an accurate map of the ionosphere TEC, in the region local to the receiver, without the need for a network of receivers and in the absence of knowledge of the receiver hardware induced bias. This thesis describes the algorithm, its implementation, and attempts to validate the method through comparison with incoherent scatter radar (ISR) data from low, mid, and high latitude locations.

In this thesis, various pilot symbol aided channel estimation and tracking methods are investigated and their performances are compared for an OFDM system with packet based communication on HF channel. For the HF channel, Watterson HF channel model is used. The compared methods are least squares (LS) channel estimation, linear minimum mean square error (LMMSE) channel estimation, least mean squares (LMS) channel tracking, recursive least squares (RLS) channel tracking, constant position model based Kalman filter channel tracking, and constant velocity model based Kalman filter channel tracking. For LMS and RLS methods some adaptive approaches are also investigated.

Le sujet de la these est l'estimation des parametres d'un modele de canal ionospherique. L'objectif de notre travail est d'ameliorer les procedures de selection automatique de canal dans les protocoles de communications hautes frequences (hf). Compte tenu des effets dispersifs introduits par le milieu de propagation (l'ionosphere) : multi-trajets et evanouissement du signal, les parametres a estimer sont les suivants : le nombre de trajets, les retards et les puissances des trajets propages et les decalages et etalements spectraux generes par les gains multiplicatifs aleatoires associes a chaque trajet. La premiere partie est consacree a la caracterisation des transmissions hf afin de determiner les causes des dispersions temporelles et frequentielles subies par les signaux de communication et d'apprehender les differents moyens mis en oeuvre pour modeliser et simuler ces effets. Notre interet s'est porte sur le modele le plus couramment utilise jusqu'a present : le modele de watterson. La deuxieme partie aborde le probleme de l'estimation de parametres de formes d'ondes retardees. Nous presentons differentes methodes qui visent a estimer un ou plusieurs retards : les methodes basees sur l'intercorrelation generalisee, celles basees sur les statistiques d'ordre superieurs ainsi que les approches geometriques. La derniere partie est consacree a l'application de ces methodes aux communications hf. Nous testons la robustesse des differentes methodes d'estimation de retards en presence de gains multiplicatifs sur chaque trajet, nous presentons un exemple de forme d'onde utilisee en communications hf (stanag 4285) et dimensionnons les methodes d'estimation en fonction de cette forme d'onde. Les performances des techniques sont evaluees sur des signaux reels ou sur des simulations de canaux ionospheriques provenant de modeles deterministes et statistiques couples a des mesures issues d'un analyseur de liaisons.

abstract: The goal is to provide accurate measurement of the channel between a ground source and a receiving satellite. The effects of the the ionosphere for ground to space propagation for radio waves in the 3-30 MHz HF band is an unstudied subject. The effects of the ionosphere on radio propagation is a long studied subject, the primary focus has been ground to ground by means of ionospheric reflection and space to ground corrections of ionospheric distortions of GPS. Because of the plasma properties of the ionosphere there is a strong dependence on the frequency of use. GPS L1 1575.42 MHz and L2 1227.60 MHz are much less effected than the 3-30 MHz HF band used for skywave propagation. The channel between the ground transmitter and the satellite receiver is characterized by 2 unique polarization modes with respective delays and Dopplers. Accurate estimates of delay and Doppler are done using polynomial fit functions. The application of polarimetric separation of the two propagating polarizations allows improved estimate quality of delay and Doppler of the respective mode. These methods yield good channel models and an effective channel estimation method well suited for the ground to space propagation.
Dissertation/Thesis
Masters Thesis Electrical Engineering 2017

The low latitude tropical ionosphere has been investigated by various researchers using Global Positioning System (GPS). Presently for many civil aviation applications, the ionospheric modeling of the tropical region has gained importance, in particular for flight safety. Since ionosphere is dispersive in nature, dual frequency (L1 = 1575.42 MHz and L2 = 1227.60 MHz) GPS observations can be used to obtain Ionospheric Total Electron Content (TEC). Since TEC varies with local time and geomagnetic latitude, an Ionospheric Modeling Technique using spatial linear approximation of vertical TEC over receiver station has been implemented following Sardon et al. The effects of all the systematic errors due to the satellite plus the receiver (SPR) instrumental biases can reach upto several nanoseconds. (1 TEC is 1016 electrons/m2, 1 ns = 2.86 TEC and 1 TEC = 0.16 m). Hence, to have an accurate estimation of ionospheric TEC, the instrumental biases must also be estimated. This thesis describes a heuristic adaptive Kalman Filtering scheme developed to estimate the TEC, the constants in the linearisation scheme, as well as the above total instrumental biases. The Kalman filter implementation is basically an optimization problem of minimizing the Cost Function J based on the difference between the model output and the measurement, called as the ‘innovation’, scaled by its covariance. In order to obtain the best possible results using the Kalman Filter approach, it is essential to provide appropriate values for the initial state, process and measurement noise covariances (P0, Q and R) respectively, which in general may not be known. Usually manual tuning of the filter parameter is carried out without using the above cost function J! The filter estimates can be highly sensitive to the above chosen statistics and thus these will have to be estimated carefully. Hence, we have utilized the Adaptive Kalman Filtering procedure of Myers and Tapley extended by Gemson and Ananthasayanam. The minimization is carried out by simultaneously estimating the above statistics and the unknown parameters, which include the TEC and the instrumental bias. In addition, A Constant Gain Kalman Filter approach using Genetic Algorithm (GA) has also been developed for the above requirement. It is observed that the steady state gains in KF and AKF approaches are in good match with the constant gains obtained from Genetic Algorithm. Using the above Adaptive Kalman Filtering technique and Constant Gain Kalman Filter approach, vertical TEC values and SPR biases have been estimated from the IGS receiver observations stationed at ISTRAC/ISRO, Bangalore, India. A diurnal TEC variation over Bangalore for a period of one year for 2003 and January 2004 is estimated and reported in this thesis. This approach has also been applied to study the behaviour of the ionosphere over low latitude IGS station at Fortaleza, Brazil data during the great magnetic storm on the 15th July 2000 and the results were found to be consistent with the results of Basu et al. In addition, Using Constant Kalman filter, the TEC enhancement over Indian region has been estimated for the October 2003 Ionospheric storm, and the results were found to be consistent with the reported results in the literature.

abstract: Earth-system models describe the interacting components of the climate system and technological systems that affect society, such as communication infrastructures. Data assimilation addresses the challenge of state specification by incorporating system observations into the model estimates. In this research, a particular data assimilation technique called the Local Ensemble Transform Kalman Filter (LETKF) is applied to the ionosphere, which is a domain of practical interest due to its effects on infrastructures that depend on satellite communication and remote sensing. This dissertation consists of three main studies that propose strategies to improve space- weather specification during ionospheric extreme events, but are generally applicable to Earth-system models: Topic I applies the LETKF to estimate ion density with an idealized model of the ionosphere, given noisy synthetic observations of varying sparsity. Results show that the LETKF yields accurate estimates of the ion density field and unobserved components of neutral winds even when the observation density is spatially sparse (2% of grid points) and there is large levels (40%) of Gaussian observation noise. Topic II proposes a targeted observing strategy for data assimilation, which uses the influence matrix diagnostic to target errors in chosen state variables. This strategy is applied in observing system experiments, in which synthetic electron density observations are assimilated with the LETKF into the Thermosphere-Ionosphere- Electrodynamics Global Circulation Model (TIEGCM) during a geomagnetic storm. Results show that assimilating targeted electron density observations yields on average about 60%–80% reduction in electron density error within a 600 km radius of the observed location, compared to 15% reduction obtained with randomly placed vertical profiles. Topic III proposes a methodology to account for systematic model bias arising ifrom errors in parametrized solar and magnetospheric inputs. This strategy is ap- plied with the TIEGCM during a geomagnetic storm, and is used to estimate the spatiotemporal variations of bias in electron density predictions during the transitionary phases of the geomagnetic storm. Results show that this strategy reduces error in 1-hour predictions of electron density by about 35% and 30% in polar regions during the main and relaxation phases of the geomagnetic storm, respectively.
Dissertation/Thesis
Doctoral Dissertation Applied Mathematics 2018

碩士
國立中央大學
太空科學研究所
99
High-frequency (HF) radio propagation through the ionosphere offers long-distance communication. Theoretically, radio intensity is decreased with increasing path and is affected also in different media. Therefore, it is important to estimate wave-propagation loss for HF communication. We have applied wave intensity equation which combines basic free-space path loss, equipment gain and the ionosphere loss quoted from IONCAP model. Then we compared the estimations with the measurements from the ChungLi dynasonde. From the comparisons, the results show that the estimations are less than the measurements in daytime but larger after 15:30 local time. Meanwhile, the results show a propagation loss around 90 to 120 dB in vertical sounding above ChungLi. Considering local background noises and distinguishing threshold from system, the ChungLi dynasonde system has to provide more than 50 dBW efficient radio power that radio waves can be successfully measured.

碩士
國立臺灣海洋大學
通訊與導航工程系
96
The purpose of this thesis is to derive, by using the concept of wide area differential GPS(WADGPS),an ionospheric delay model that is well suitable for using in Taiwan`s Flight information region(FIR). We computed Ionospheric Grid Point (IGP) vertical delay by using inverse distance weighted algorithm, and construct three dimension ionosphere grid model of Taiwan. The partitioned interval of the ionospheric grid point is considered for two cases: the first one is 5 degree, the second one is 2.5 degree. In both cases, the results are further used to perform a stand-alone GPS positioning, and then use the result of the positioning to analyze the most suitable size of the grid point for using in Taiwan area.

碩士
國立成功大學
測量及空間資訊學系碩博士班
96
Global Positioning System (GPS) has been known as a high-precision positioning technology. Traditionally, dual frequency equipments provide more accurate positioning; however, they are more expensive than single frequency equipments. Therefore, we hope that positioning accuracy derived from single frequency observations could be the same as dual frequency observations by improving ionospheric correction. The ionospheric delay is currently the primary error of GPS single frequency positioning. Although the Global Ionospheric Model provided by IGS is available for correcting the ionospheric delay, its resolution is too coarse to present the iononspheric activation in Taiwan area. This study focus on the estimation of a Taiwan ionospheric model in terms of spherical harmonic coefficients using the GPS geometry-free observations derived from 2006 e-GPS data provided by National Land Surveying and Mapping Center. A comparison of total electron content difference between the IGS model and the Taiwan local ionospheric model at a specific location (longitude: 120E, Latitude: 22.5N) shows the RMS is 3~8 TECU and the maximum RMS happens at 12:00~18:00 while the ionosphere is extremely active. Different ionospheric models used for single frequency Precise Point Positioning were tested at different time intervals. Positioning accuracy is improved by 50% using the IGS model compared with no ionospheric model involved. Using the Taiwan ionospheric model can improve the positioning accuracy by 80~90% compared with using the IGS model, and the improvement is significant at 12:00~18:00 time interval. Additionally, if a whole day GPS data are adopted in the test, positioning error is at meter level by applying the IGS model, while positioning error can reach 5 cm in horizontal and 15 cm in vertical after the Taiwan ionospheric model is corrected. In conclusion, the Taiwan ionospheric model used for single frequency Precise Point Positioning has centimeter-level horizontal positioning error and decimeter-level vertical positioning error, which is better than using the IGS model.