Abstract
Properties of the Householder transformation and its application to square-root information filtering (SRIF) are reviewed. The Householder algorithm is used to arrive at an improved SRIF mechanization for the case of coloured noise. It is also used to construct an error analysis algorithm which accounts for the use of incorrect a priori statistics in the SRIF. The results illustrate that (in addition to the numerical attributes of square-root filtering) the SRIF is a flexible, convenient error analysis tool.
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