Tesi etd-05182016-101706 |
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Tipo di tesi
Tesi di laurea magistrale
Autore
FORCONI, MARCO
URN
etd-05182016-101706
Titolo
Development of Kalman Filters for Navigation and Flow Angles Calibration of Air Data Systems
Dipartimento
INGEGNERIA CIVILE E INDUSTRIALE
Corso di studi
INGEGNERIA AEROSPAZIALE
Relatori
relatore Ing. Schettini, Francesco
relatore Prof. Galatolo, Roberto
relatore Prof. Denti, Eugenio
relatore Ing. Di Rito, Gianpietro
relatore Prof. Galatolo, Roberto
relatore Prof. Denti, Eugenio
relatore Ing. Di Rito, Gianpietro
Parole chiave
- calibrazione
- dati aria
- derapata
- filtro di kalman
- GPS
- identificazione vento
- incidenza
- INS
Data inizio appello
14/06/2016
Consultabilità
Non consultabile
Data di rilascio
14/06/2086
Riassunto
The theme of this work is the calibration of air data probes, in particular the calibration of angles of attack and sideslip. These calibrations are usually lead installing a nose-boom on the aircraft nose a boom where many probes such as pitots and angular sensors are mounted. Since obtained data can be considered undisturbed by aircraft fuselage, it is possible to derive the calibration functions relating the probes measurements with the real aircraft flow angles.
The target of this work is to develop a new method in which a boom is not adopted, leading to great reduction of time and costs. In particular, the developed method bases on Inertial Measurement Unit, GPS data and the air-relative speed which are elaborated by Kalman Filters that allows to obtain the wind components estimation and the navigation parameters.
The performance of the Kalman filters is tested by applying them to real flight data from two very different aeroplanes, an unmanned MALE (Medium Altitude Long Range) aircraft and an advanced high performance jet trainer.
The target of this work is to develop a new method in which a boom is not adopted, leading to great reduction of time and costs. In particular, the developed method bases on Inertial Measurement Unit, GPS data and the air-relative speed which are elaborated by Kalman Filters that allows to obtain the wind components estimation and the navigation parameters.
The performance of the Kalman filters is tested by applying them to real flight data from two very different aeroplanes, an unmanned MALE (Medium Altitude Long Range) aircraft and an advanced high performance jet trainer.
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