Data fusion versus passive filtering for angular velocity estimation

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.