The TRIAD algorithm as maximum likelihood estimation

The TRIAD algorithm is shown to be derivable as a maximum-likelihood estimator. In particular, using the QUEST measurement model, the TRIAD attitude error covariance matrix can be derived as the inverse of the Fisher information matrix. The treatment here gives a microscopic analysis of the algorithm and its connection to the QUEST algorithm. It also sheds valuable light on the origin of discrete degeneracies in deterministic attitude estimation.

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