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• W1489416677 abstract "The 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." @default.
• W1489416677 created "2016-06-24" @default.
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• W1489416677 creator A5065223137 @default.
• W1489416677 date "1999-01-01" @default.
• W1489416677 modified "2023-09-27" @default.
• W1489416677 title "How to Estimate Attitude from Vector Observations" @default.
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