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Estimating of motion models and its parameters to identify target trajectory
 Benko, Matej ; Eliaš, Michal (oponent) ; Žák, Libor (vedoucí práce)
This text deals with removing noise from inaccurate multilateration measurements. It is used Bayesian estimation theory to find the posterior density of the real position (or, moreover, velocity) of an airplane. Together with true position, we estimate on Bayesian principle the geometry of a maneuver that an airplane obeys and so-called process noise, which describes how much an airplane's trajectory differs from the geometry. The estimation of the process noise is the essential part of the work. It is derived Bayesian approach together with the maximum likelihood approach. Then, improvements to these algorithms are introduced. They provide better results in particular cases, such as a maneuver change of the target or initial uncertainty of the maximum likelihood estimation. At the end of the text, the possibility of a combination of geometry and process noise estimation is described.
Úplný záznam
Estimating of motion models and its parameters to identify target trajectory
 Benko, Matej ; Eliaš, Michal (oponent) ; Žák, Libor (vedoucí práce)
This text deals with removing noise from inaccurate multilateration measurements. It is used Bayesian estimation theory to find the posterior density of the real position (or, moreover, velocity) of an airplane. Together with true position, we estimate on Bayesian principle the geometry of a maneuver that an airplane obeys and so-called process noise, which describes how much an airplane's trajectory differs from the geometry. The estimation of the process noise is the essential part of the work. It is derived Bayesian approach together with the maximum likelihood approach. Then, improvements to these algorithms are introduced. They provide better results in particular cases, such as a maneuver change of the target or initial uncertainty of the maximum likelihood estimation. At the end of the text, the possibility of a combination of geometry and process noise estimation is described.
Úplný záznam

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