DocumentCode :
3132616
Title :
Estimation design of MEMS-based inertial navigation systems with noise coupling input saturation: Robust approach
Author :
Chen, Yung-Yue ; Chang, Shyang-Jye ; Chen, Yung-Hsiang
Author_Institution :
Micro Sensing Applic. Dept M500, Microsyst. Technol. Center, Taiwan
fYear :
2009
fDate :
21-23 Oct. 2009
Firstpage :
718
Lastpage :
721
Abstract :
There are, in practice, so many control systems possesses this kind of special feature, e.g., ballistic missile´s maneuver couples with wind gusts, acceleration signal measured by accelerometers couples with the external and internal noises, and so on. Generally, the input signal u(k) is always assumed as an exactly known variable and never corrupted with noise; hence one is capable of dealing with these kinds of estimation problems by the well-known Kalman Filter that is widely used in the state estimation. Of course, it is no doubt that in the presence of unknown noise coupling input saturations, performance of Kalman Filter will be seriously degraded since the unknown input saturations coupling with input noises appear on a system model as extensive noises, and the constant processing noise variance will be not capable of covering it because of the time-variant character of these type signals.
Keywords :
Kalman filters; estimation theory; inertial navigation; micromechanical devices; state estimation; Kalman filter; MEMS-based inertial navigation systems; constant processing noise variance; control systems; estimation problems; state estimation; time-variant character; unknown noise coupling input saturations; Inertial navigation; Noise robustness;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Microsystems, Packaging, Assembly and Circuits Technology Conference, 2009. IMPACT 2009. 4th International
Conference_Location :
Taipei
Print_ISBN :
978-1-4244-4341-3
Electronic_ISBN :
978-1-4244-4342-0
Type :
conf
DOI :
10.1109/IMPACT.2009.5382288
Filename :
5382288
Link To Document :
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