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How to Estimate Attitude from Vector ObservationsThe most robust estimators minimizing Wahba's loss function are Davenport's q method and the Singular Value Decomposition (SVD) method. The q method is faster than the SVD method with three or more measurements. The other algorithms are less robust since they solve the characteristic polynomial equation to find the maximum eigenvalue of Davenport's K matrix. They are only preferable when speed or processor power is an important consideration. Of these, Fast Optimal Attitude Matrix (FOAM) is the most robust and faster than the q method. Robustness is only an issue for measurements with widely differing accuracies, so the fastest algorithms, Quaternion ESTimator (QUEST), EStimator of the Optimal Quaternion (ESOQ), and ESOQ2, are well suited to star sensor applications.
Document ID
Document Type
Conference Paper
Markley, F. Landis (NASA Goddard Space Flight Center Greenbelt, MD United States)
Mortari, Daniele (Rome Univ. Rome, Italy)
Date Acquired
September 6, 2013
Publication Date
January 1, 1999
Subject Category
Earth Resources and Remote Sensing
Meeting Information
Astrodynamics Specialist(Girdwood, AK)
Distribution Limits
Work of the US Gov. Public Use Permitted.

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NameType 19990104598.pdf STI