Zugl.: Stuttgart, Univ., Diss., 2001.

This research effort is concerned with the methods of simplified orbit determination and orbit representation and their applications for Low Earth Orbit (LEO) satellite missions, particularly addressing the operational needs of the FedSat mission. FedSat is the first Australian-built satellite in over thirty years. The microsatellite is approximately 50cm cubed with a mass of 58 kg. The satellite was successfully placed into a low-earth near-polar orbit at an altitude of 780km by the Japanese National Space Development Agency (NASDA) H-IIA launch vehicle on 14, December 2002. Since then, it has been streaming scientific data to its ground station in Adelaide almost daily. This information is used by Australian and international researchers to study space weather, to help improve the design of space computers, communication systems and other satellite technology, and for research into navigation and satellite tracking. This research effort addresses four practical issues regarding the FedSat mission and operations. First, unlike most satellite missions, the GPS receiver onboard FedSat operates in a duty-cycle mode due to the limitations of the FedSat power supply. This causes significant difficulties for orbit tracking, Precise Orbit Determination and scientific applications. A covariance analysis was performed before the mission launch to assess the orbit performance under different operational modes. The thesis presents the analysis methods and results. Second, FedSat supports Ka-band tracking experiments that require a pointing accuracy of 0.03 degree. The QUT GPS group is obligated to provide the GPS precise orbit solution to meet this requirement. Ka-band tracking requests satellite orbital position at any instant time with respect to any of the observation stations. Because orbit determination and prediction software only provide satellite orbital data at a discrete time point, it is necessary to find a way to represent the satellite orbit as a continuous trajectory with discrete observation data, able to obtain the position of the satellite at the time of interest. For this purpose, an orbit interpolation algorithm using the Chebyshev polynomial was developed and applied to Ka-band tracking applications. The thesis will describe the software and results. Third, since the launch of FedSat, investigators have received much flight GPS data. Some research was invested in the analysis of FedSat orbit performance, GPS data quality and the quality of the onboard navigation solutions. Studies have revealed that there are many gross errors in the FedSat onboard navigation solution (ONS). Although the 1-sigma accuracy of each component is about 20 m, there are more than 11 %positioning errors that fall outside +/-50m, and 5% of the errors are outside the 100mbound. The 3D RMS values would be 35m, 87m, and 173m for the above three cases respectively. The FedSat ONS uncertainties are believed to be approximately three times greater than those from other satellite missions. Due to the high percentage of outlier solutions, it would be dangerous to use these without first applying data detection and exclusion procedures. Therefore, this thesis presents two simplified orbit determination methods that can improve the ONS. One is the &quotgeometric method", which makes use of delta-position solutions derived from carrier phase differences between two epochs to smooth the code-based navigation solutions. The algorithms were tested using SAC-C GPS data and showing some improvement. The second method is the &quotdynamic method", which uses orbit dynamics information for orbit improvements. Fourth, the FedSat ground tracking team at Adelaide use the NORAD TLE orbit for daily FedSat tracking. Research was undertaken to convert an orbit trajectory into these Two Line Elements (TLE). Algorithms for the estimation of TLE solutions from the FedSat onboard GPS navigation solutions are outlined. Numerical results have shown the effects of the unmodelled forces/perturbations in the SPG4 models for the FedSat orbit determination would reach a level of ±1000m. This only includes the orbit representation errors with TLE data sets. The total FedSat orbit propagation should include both the orbit propagation and orbit representation terms. The analysis also demonstrates that the orbit presentation error can be reduced to ±200m and ±100mlevels with the EGM4x4 and EGM10x10 gravity field models respectively. This can meet the requirements for Ka-band tracking. However, a simplified tracking program based on numerical integration has to be developed to replace the SPG4 models.

This diploma thesis deals with the GPS navigations and their applications for portable phones and other portable devices. The thesis is divided into the theoretical and the practical part. In the theoretical part, the necessary terminology is defined. Further on, the different types of the GPS navigations are examined along with their applications and their particular advantages and disadvantages. A reader of this thesis will learn about the basic principles of how the GPS navigations work. In the practical part, the research part, the particular GPS devices undergo tests that had been based on particular hypotheses and that had been run according to predetermined conditions. The crucial part of this section is a comparison different types of GPS navigations with the GPS navigation Waze which has introduced an innovative approach to the creation of its content by the users themselves.

No description available.

No description available.

Relative global positioning system (GPS) navigation is currently used for autonomous rendezvous and docking of two spacecraft as well as formation flying applications. GPS receivers deliver measurements to flight software that use this information to determine estimates of the current states of the spacecraft. The success of autonomous proximity operations in the presence of an uncertain environment and noisy measurements depends primarily on the navigation accuracy. This thesis presents the implementation and calibration of a spaceborne GPS receiver model, a visibility analysis for multiple GPS antenna cone angles, the implementation of four different extended Kalman filter architectures and a comparison of the advantages and disadvantages of each filter used for relative GPS navigation. A spaceborne GPS model is developed to generate simulated GPS measurements for a spacecraft located on any orbit around the Earth below the GPS constellation. Position and velocity estimation algorithms for GPS receivers are developed and implemented. A visibility analysis is performed to determine the number of visible satellites throughout the duration of the rendezvous. Multiple constant fields of view are analyzed and results compared to develop an understanding of how the GPS constellation evolves during the proximity operations. The comparison is used to choose a field of view with adequate satellite coverage. The advantages and disadvantages of the relative navigation architectures are evaluated based on a trade study involving several parameters. It is determined in this thesis that a reduced pseudorange filter provides the best overall performance in both relative and absolute navigation with less computational cost than the slightly more accurate pseudorange lter. A relative pseudorange architecture experiences complications due to multipath rich environments and performs well in only relative navigation. A position velocity architecture performs well in absolute state estimation but the worst of the four filters studied in relative state estimation.

This thesis presents new evidences of negative impacts of traffic congestion in São Paulo Metropolitan Area, indicating that the omission or retardation of policy to alleviate that charges society with a high cost. Besides that, we shed light on Waze application\'s impacts, evidencing GPS-based participatory navigation is a key element of the traffic in the contemporary cities. Induced by the economic theory, one can see that traffic slowness derived from the general demand for automotive vehicles corresponds to a social cost. With the objective of translating this cost to monetary units, we developed an approach that matches the 2012 Origin-Destination survey to Google Maps data. An econometric travel mode choice model is estimated and through that we infer the Value of Time for trips. From counterfactual analysis for travel duration, we estimate the delays of the trips in relation to a hypothetic free flow situation. Joining the calculations, we estimate that 89% of the trips motivated by work in São Paulo are retarded by traffic frictions, generating an annual welfare cost that amounts to R$7.338 billions. Additionally, we analyze widespread Waze malfunctioning at 10/23/2017. Combining congestion data to the Value of Time, we estimate that the Waze bug approximatedely tripled the welfare costs in regards to a typical day, showing the magnitude of mass effects that a social navigation application is able to trigger. / Esta dissertação traz novas evidências dos efeitos negativos do congestionamento do trânsito na Região Metropolitana de São Paulo, mostrando que a morosidade na implantação de soluções custa muito caro para a sociedade. Além disso, evidências empíricas dos impactos do aplicativo Waze são elucidadas, mostrando que a navegação participativa por meio de aparelhos com GPS não pode ser esquecida ao pensarmos o trânsito nas cidades contemporâneas. À luz da teoria econômica, é possível ver que a lentidão do trânsito proveniente da demanda coletiva por automóveis corresponde a um custo social. Para quantificar este custo em unidades monetárias, é desenvolvida uma abordagem que combina dados da Pesquisa de Mobilidade de 2012 com dados do Google Maps. Através de um modelo econométrico de escolha de modal de transporte, são inferidos os valores do tempo em viagem e, através da análise contrafactual da duração dos deslocamentos, é estimado o tempo de atraso das viagens em relação a uma situação hipotética de fluxo livre. Juntando os cálculos, é estimado que 89% das viagens motivadas por trabalho em São Paulo são atrasadas por fricções do tráfego, gerando um custo de bem-estar da ordem de R$7,338 bilhões por ano. Ademais, são analisados empiricamente os impactos de uma falha generalizada do Waze ocorrida em 23/10/2017. Combinando dados de congestionamento com os valores de tempo já inferidos, é estimado que a falha aproximadamente triplicou os custos de bem-estar em relação a um dia típico, dando magnitude aos efeitos de massa que um aplicativo de navegação social é capaz de provocar.

This thesis presents new evidences of negative impacts of traffic congestion in São Paulo Metropolitan Area, indicating that the omission or retardation of policy to alleviate that charges society with a high cost. Besides that, we shed light on Waze application\'s impacts, evidencing GPS-based participatory navigation is a key element of the traffic in the contemporary cities. Induced by the economic theory, one can see that traffic slowness derived from the general demand for automotive vehicles corresponds to a social cost. With the objective of translating this cost to monetary units, we developed an approach that matches the 2012 Origin-Destination survey to Google Maps data. An econometric travel mode choice model is estimated and through that we infer the Value of Time for trips. From counterfactual analysis for travel duration, we estimate the delays of the trips in relation to a hypothetic free flow situation. Joining the calculations, we estimate that 89% of the trips motivated by work in São Paulo are retarded by traffic frictions, generating an annual welfare cost that amounts to R$7.338 billions. Additionally, we analyze widespread Waze malfunctioning at 10/23/2017. Combining congestion data to the Value of Time, we estimate that the Waze bug approximatedely tripled the welfare costs in regards to a typical day, showing the magnitude of mass effects that a social navigation application is able to trigger. / Esta dissertação traz novas evidências dos efeitos negativos do congestionamento do trânsito na Região Metropolitana de São Paulo, mostrando que a morosidade na implantação de soluções custa muito caro para a sociedade. Além disso, evidências empíricas dos impactos do aplicativo Waze são elucidadas, mostrando que a navegação participativa por meio de aparelhos com GPS não pode ser esquecida ao pensarmos o trânsito nas cidades contemporâneas. À luz da teoria econômica, é possível ver que a lentidão do trânsito proveniente da demanda coletiva por automóveis corresponde a um custo social. Para quantificar este custo em unidades monetárias, é desenvolvida uma abordagem que combina dados da Pesquisa de Mobilidade de 2012 com dados do Google Maps. Através de um modelo econométrico de escolha de modal de transporte, são inferidos os valores do tempo em viagem e, através da análise contrafactual da duração dos deslocamentos, é estimado o tempo de atraso das viagens em relação a uma situação hipotética de fluxo livre. Juntando os cálculos, é estimado que 89% das viagens motivadas por trabalho em São Paulo são atrasadas por fricções do tráfego, gerando um custo de bem-estar da ordem de R$7,338 bilhões por ano. Ademais, são analisados empiricamente os impactos de uma falha generalizada do Waze ocorrida em 23/10/2017. Combinando dados de congestionamento com os valores de tempo já inferidos, é estimado que a falha aproximadamente triplicou os custos de bem-estar em relação a um dia típico, dando magnitude aos efeitos de massa que um aplicativo de navegação social é capaz de provocar.

The project explores the possibilities on how to improve the accuracy of GPS velocity data by using sensor fusion with an extended Kalman filter. The proposed solution in this project is a sensor fusion between the GPS and IMU of the system, where the extended Kalman filter was used to estimate the velocity from the sensor data. The hardware used for the data acquisition to the proposed solution was a Pixhawk 4 (PX4), which has an IMU consisting of accelerometers, gyroscopes and magnetometers. The PX4:s corresponding GPS module was also used to collect accurate velocity data. The data was logged using Simulink and later processed with MATLAB. The sensor fusion using the extended Kalman filter gave good estimates upon constant acceleration but had problems with estimating over varying acceleration. This was initially planned to be solved using smoothing filters, which is an essential part of the fusion process, but was never implemented due to time constraints. The constructed filter acts as a foundation towards future improvement. Other methods such as unscented Kalman filter, particle filter and neural network could also be explored to improve the estimation of the velocity due to these filters being known to have better performance. However, most of these alternatives need more computing power and are generally harder to implement compared to the extended Kalman filter. This project would be beneficial to QTAGG, since increasing the velocity resolution and accuracy of the system can provide possibilities of better optimization. It is also a commonly implemented solution where there are many state of the art implementations available.

This thesis deals with the new unconventional way of agricultural land management. Currently, high precision of work machines in the field is required. The development and accessibility of modern agricultural equipment linked to the information technology has led this branch to the unnecessary and high precise field ecosystem management. This new approach is called as precision agriculture. In the theoretical part of work is made the literature research and overview of the available data about the precision farming methods and the possibilities of field observation and data collection, including their processing with the available high information technology. The practical part evaluates the current possibilities of precision farming in the Czech Republic and in the world and looks for a solution to its implementation in the specific business environment of the agricultural laboratory.