DocumentCode :
2292371
Title :
Data fusion versus passive filtering for angular velocity estimation
Author :
Bar-Itzhack, Itzhack Y.
Author_Institution :
Fac. of Aerosp. Eng., Technion-Israel Inst. of Technol., Haifa, Israel
Volume :
2
fYear :
2000
fDate :
10-13 July 2000
Abstract :
Scanning the known algorithms for deriving the angular velocity vector from either vector measurements or attitude measurements it is realized that the algorithms are divided into two categories, each category employing a different approach. One category requires the use of a low-pass filter and one does not. In this paper the two categories are formulated in general terms, which enables the presentation of the connection and comparison between them. The conclusions are demonstrated through examples.
Keywords :
Kalman filters; angular velocity; attitude measurement; differentiation; low-pass filters; sensor fusion; angular velocity estimation; attitude measurements; data fusion; low-pass filter; passive filtering; vector measurements; Active filters; Aerospace engineering; Angular velocity; Filtering; Kalman filters; Low pass filters; Passive filters; Riccati equations; Space vehicles; Velocity measurement;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information Fusion, 2000. FUSION 2000. Proceedings of the Third International Conference on
Conference_Location :
Paris, France
Print_ISBN :
2-7257-0000-0
Type :
conf
DOI :
10.1109/IFIC.2000.859848
Filename :
859848
Link To Document :
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