Absolute position estimation is nowadays globally and always available due to Global Navigation Satellite Systems, like the Global Position System (GPS). Because of several error sources and other influences, the accuracy is limited or the signal may be blocked completely. Sensor fusion techniques are used to achieve better accuracy and to increase reliability. The most common integration method is an inertial navigation system (INS) aided with GPS measurements, processed by a Kalman filter. In this work two different GPS/INS integration methods are implemented, utilizing inertial sensors, odometer data and GPS measurements. The algorithms are designed to keep the computational complexity low and to be suitable for real time applications. The multi-rate property of the sensors is considered as well. Also an inertial sensor error analysis is performed. The results are presented by a MATLAB simulation, based on prior taken measurement data sets.
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Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Absolute position estimation is nowadays globally and always available due to Global Navigation Satellite Systems, like the Global Position System (GPS). Because of several error sources and other influences, the accuracy is limited or the signal may be blocked completely. Sensor fusion techniques are used to achieve better accuracy and to increase reliability. The most common integration method is an inertial navigation system (INS) aided with GPS measurements, processed by a Kalman filter. In this work two different GPS/INS integration methods are implemented, utilizing inertial sensors, odometer data and GPS measurements. The algorithms are designed to keep the computational complexity low and to be suitable for real time applications. The multi-rate property of the sensors is considered as well. Also an inertial sensor error analysis is performed. The results are presented by a MATLAB simulation, based on prior taken measurement data sets. 124 pp. Englisch. Nº de ref. del artículo: 9783639882032
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Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Neubauer LukasLukas Neubauer, born in 1989, M.Sc. 2009-2015 Electrical Engineering at Graz University of Technology with specialisation on Automation Engineering and Mechatronics. Master s Thesis: Absolute Position Est. Nº de ref. del artículo: 157929909
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Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Absolute position estimation is nowadays globally and always available due to Global Navigation Satellite Systems, like the Global Position System (GPS). Because of several error sources and other influences, the accuracy is limited or the signal may be blocked completely. Sensor fusion techniques are used to achieve better accuracy and to increase reliability. The most common integration method is an inertial navigation system (INS) aided with GPS measurements, processed by a Kalman filter. In this work two different GPS/INS integration methods are implemented, utilizing inertial sensors, odometer data and GPS measurements. The algorithms are designed to keep the computational complexity low and to be suitable for real time applications. The multi-rate property of the sensors is considered as well. Also an inertial sensor error analysis is performed. The results are presented by a MATLAB simulation, based on prior taken measurement data sets.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 124 pp. Englisch. Nº de ref. del artículo: 9783639882032
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Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Absolute position estimation is nowadays globally and always available due to Global Navigation Satellite Systems, like the Global Position System (GPS). Because of several error sources and other influences, the accuracy is limited or the signal may be blocked completely. Sensor fusion techniques are used to achieve better accuracy and to increase reliability. The most common integration method is an inertial navigation system (INS) aided with GPS measurements, processed by a Kalman filter. In this work two different GPS/INS integration methods are implemented, utilizing inertial sensors, odometer data and GPS measurements. The algorithms are designed to keep the computational complexity low and to be suitable for real time applications. The multi-rate property of the sensors is considered as well. Also an inertial sensor error analysis is performed. The results are presented by a MATLAB simulation, based on prior taken measurement data sets. Nº de ref. del artículo: 9783639882032
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