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- W379539426 abstract "The Satellite based navigation systems are often integrated with inertial navigation systems in order to provide greater accuracy and reliability in the position and velocity parameters. For this purpose high quality inertial sensors are used which can provide real-time navigation at centimeter level. Price, size and weight of traditional INS has been a problem which has been solved successfully by the use of Micro Electro Mechanical Sensors (MEMS). The problem with the MEMS technology is the large error which grows rapidly and degrade the performance of the navigation system. Different methods are used to calculate the error coefficients (not implemented in this study work) which are further used in a kalman filter in order to enhance the performance of the system. Thus a kalman filter has been introduced to perform the data fusion algorithms. Kalman filtering is a recursive technique used to optimize the state vector of the estimates and it efficiently provides the navigation estimates of a dynamic system. All the navigation data used in this thesis work has been provided by my supervisor, professor Jon Glenn Gjevestad (UMB). A real-time system has been tested in the urban areas for different scenarios. Kalman filter approach with loose integration has been implemented. A comparison of the filtered solution with the reference positions has been made by introducing a 2D horizontal position error in order to analyze the position accuracy. In the end some recommendations on future work are courted." @default.
- W379539426 created "2016-06-24" @default.
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- W379539426 date "2014-01-01" @default.
- W379539426 modified "2023-09-28" @default.
- W379539426 title "GNSS/INS Integration in Urban Areas" @default.
- W379539426 hasPublicationYear "2014" @default.
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