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In Intelligent Transport Systems (ITS), specifically in autonomous driving operations, accurate vehicle localization is essential for safe operations. The localization accuracy depends on both position and positioning error estimates. Technologies aiming to improve positioning error estimation are required and are currently being researched. This project has investigated machine learning algorithms applied to positioning error estimation by assessing relevant information obtained from a GNSS receiver and adding environmental information  coming from a camera mounted on a radio controlled vehicle testing platform. The research was done in two stages. The first stage consists of the machine learning algorithms training and testing on existing GNSS data coming from Waysure´s data base from tests ran in 2016, which did not consider the environment surrounding the GNSS receiver used during the tests. The second stage consists of the machine learning algorithms training and testing on GNSS data coming from new test runs carried on May 2019, which include the environment surrounding the GNSS receiver used. The results of both stages are compared. The relevant features are obtained as a result of the machine learning decision trees algorithm and are presented. This report concludes that there is no statistical evidence indicating that the tested environmental input from the camera could improve positioning error estimation accuracy with the built machine learning models. / Inom Intelligenta transportsystem (ITS), specifikt för självkörande fordon, så är en exakt fordonspositionering en nödvändighet för ökad trafiksäkerhet. Positionsnoggrannheten beror på estimering av både positionen samt positionsfelet. Olika tekniker och tillämpningar som siktar på att förbättra positionsfeluppskattningen behövs, vilket det nu forskas kring. Denna uppsats undersöker olika maskininlärningsalgoritmer inriktade på estimering av positionsfel. Algoritmerna utvärderar relevant information från en GNSS-mottagare, samt information från en kamera om den kringliggande miljön. En GNSS-mottagare och kamera monterades på en radiostyrd mobil testplattform för insamling av data.  Examensarbetet består av två delar. Första delen innehåller träning och testning av valda maskininlärningsalgoritmer med GNSS-data tillhandahållen av Waysure från tester gjorda under 2016. Denna data inkluderar ingen information från den omkringliggande miljön runt GNSS-mottagaren. Andra delen består av träning och testning av valda maskininlärningsalgoritmer på GNSS-data som kommer från nya tester gjorda under maj 2019, vilka inkluderar miljöinformation runt GNSS-mottagaren. Resultaten från båda delar analyseras. De viktigaste egenskaper som erhålls från en trädbaserad modell, algoritmens beslutsträd, presenteras. Slutsatsen från denna rapport är att det inte går att statistiskt säkerställa att inkludering av information från den omkringliggande miljön från en kamera förbättrar noggrannheten vid estimering av positionsfelet med de valda maskininlärningsmodellerna.

A method for precisely synchronizing an external serial data stream to the pulse-per-second (PPS) output signal from a global navigation satellite-based system (GNSS) receiver was investigated. A signal timing device was designed that used a digital signal processor (DSP) with serial inputs and input captures to generate time stamps for asynchronous serial data based on an 58593.75 Hz internal timer. All temporal measurements were made directly in hardware to eliminate software latency. The resolution of the system was 17.1 µs, which translated to less than one millimeter of horizontal position error at travel speeds typical of most agricultural operations. The dynamic error of a TTS was determined using a rotary test fixture. Tests were performed at angular velocities ranging from 0 to 3.72 rad/s and a radius of 0.635 m. Average latency from the TTS was shown to be consistently near 0.252 s for all angular velocities and less variable when using a reflector based machine target versus a prism target. Sight distance from the target to the TTS was shown to have very little effect on accuracy between 4 and 30 m. The TTS was determined to be a limited as a position reference for dynamic GNSS and vehicle auto-guidance testing based on angular velocity. The dynamic error of a GNSS receiver was determined using the rotary test fixture and modeled as discrete probability density functions for varying angular velocities and filter levels. GNSS position and fixture data were recorded for angular velocities of 0.824, 1.423, 2.018, 2.618, and 3.222 rad/s at a 1 m radius. Filter levels were adjusted to four available settings including; no filter, normal filter, high filter, and max filter. Each data set contained 4 hours of continuous operation and was replicated three times. Results showed that higher angular velocities increased the variability of the distribution of error while not having a significant effect on average error. The distribution of error tended to change from normal distributions at lower angular velocities to uniform distributions at higher angular velocities. Internal filtering was shown to consistently increase dynamic error for all angular velocities.

Orientador: Paulo de Oliveira Camargo / Banca: João Francisco Galera Monico / Banca: Edvaldo Simões da Fonseca Junior / Banca: Cláudia Pereira Krueger / Banca: Moisés Ferreira Costa / Resumo: O erro devido à ionosfera nas observáveis GNSS (Global Navigation Satellite System) é diretamente proporcional à densidade de elétrons presente na ionosfera e inversamente proporcional a frequência do sinal. Da mesma forma que no posicionamento por ponto, os resultados obtidos no posicionamento relativo são afetados pelo efeito sistemático da ionosfera, que é uma das maiores fontes de erro no posicionamento com GNSS. Mesmo considerando que parte dos erros devido à ionosfera é cancelada na dupla diferenciação, a ionosfera pode causar fortes impactos no posicionamento relativo. O problema principal neste método de posicionamento é a variação espacial na densidade de elétrons, que pode ocorrer em função de vários fatores, tais como hora local, variação sazonal, localização do usuário, ciclo solar e atividade geomagnética. Dependendo das condições do clima espacial, que é controlado pelo Sol, a atividade geomagnética pode ser alterada de forma significativa, dando origem a uma tempestade geomagnética. Nesta pesquisa foram avaliados os efeitos da ionosfera no posicionamento relativo, com observações GNSS da fase da onda portadora (L1), nas regiões ionosféricas de latitude média e alta e na região equatorial. Nas duas primeiras regiões foram analisados os efeitos da ionosfera em períodos de irregularidades, decorrentes de tempestades geomagnéticas. Na região equatorial, que engloba o Brasil, foram analisados os efeitos da ionosfera em função da variação diária e sazonal. No processamento dos dados GNSS foi utilizado o GPSeq, que processa os dados na forma recursiva e fornece os Resíduos Preditos da Dupla Diferença da Fase (RPDDF) ... (Resumo completo, clicar acesso eletrônico abaixo) / Abstract: The error caused by ionosphere on GNSS (Global Navigation Satellite System) is directly proportional to the density of electrons from ionosphere and inversely proportional to the frequency squared of the signal GNSS. As in the case of point positioning, results in relative positioning are affected by systematic effect from ionosphere, which is one of major error sources in the GNSS positioning. Although some errors caused by ionosphere are canceled in double difference, strong impacts may be caused by ionosphere on the relative positioning. In this positioning the main problem is the spatial variation in electron density that can occur due local time, seasonal variation, user location, solar cycle, geomagnetic activity, etc. Depending on the conditions of space weather, in which is controlled by the Sun, the geomagnetic activity can be changed inducing geomagnetic storms. In this research the effects from ionosphere has been evaluated in GNSS relative positioning using L1 carrier phase observations, at the three regions of the ionosphere: middle and high latitudes and equatorial region. In regions of middle and high latitudes have been analyzed the effects from ionosphere in irregularities periods, caused by geomagnetic storms. In the equatorial region, including Brazil, have been analyzed the effects from ionosphere according daily and seasonal variation. In the processing GNSS data has been used GPSeq software. This software processes the data in a recursive form and provides the Predicted Residual of Carrier Phase Double Difference (PRCPDD) ... (Complete abstract click electronic access below) / Doutor

>Magister Scientiae - MSc / The development of regional ionospheric Total Electron Content (TEC) models has contributed to understanding the behavior of ionospheric parameters and the coupling of the ionosphere to space weather activities on both local and global scales. In the past several decades, the International Global Navigation Satellite Systems Service (GNSS) networks of dual frequency receiver data have been applied to develop global and regional models of ionospheric TEC. These models were mainly developed in the Northern Hemisphere where there are dense network of ground based GPS receivers for regional data coverage. Such efforts have been historically rare over the African region, and have only recently begun. This thesis reports the investigation of the effect of mid-latitude magnetic storms on TEC over South Africa for portions of Solar Cycles 23 and 24. The MAGIC package was used to estimate TEC over South Africa during Post Solar Maximum, Solar Minimum, and Post Solar Minimum periods. It is found that TEC is largely determined by the diurnal cycle of solar forcing and subsequent relaxation, but effects due to storms can be determined

京都大学 / 0048 / 新制・課程博士 / 博士(理学) / 甲第22256号 / 理博第4570号 / 新制||理||1656(附属図書館) / 京都大学大学院理学研究科地球惑星科学専攻 / (主査)准教授 西村 卓也, 教授 福田 洋一, 准教授 深畑 幸俊 / 学位規則第4条第1項該当 / Doctor of Science / Kyoto University / DGAM

Master’s thesis deals with global navigation satellite systems. It gathers information about operation principles of individual systems and evaluates their applicability for Air transportation through own measures.

This diploma thesis applies the well-established concept of security dilemma to the relatively new domain of outer space. It constructs a comprehensive modification of the concept for the outer space - the space security dilemma - and establishes criteria for the assessment of it while also discussing previous approaches. The thesis then applies this concept and established criteria, to the issue of Global Navigation Satellite Systems (GNSS). More specifically, it focuses on the case of the European GNSS called Galileo and assesses the intentions behind its creation. Through this assessment, the thesis focuses on determining whether the European Union became a space security dilemma initiator by the development of the Galileo system. In order to confront the theoretical conclusions with praxis, the thesis then focuses on the case of the United States of America and the confrontation between GPS and Galileo. In its last chapter, the thesis replicates this approach on the cases of the Russian Federation (and its GLONASS) and the People's Republic of China (and its BeiDou/COMPASS).

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