The treatment of bias in the square-root information filter/smoother

The Dyer-McReynolds square-root information filter (SRIF) is rederived, using recursive least-square arguments. The result is applied to a system composed partly of biases. The filtersensitivity matrix,computed covariance, andconsider covariance for this augmented system are reviewed. A new computationally attractive representation for the smoothed estimates, in terms of a smoothedsensitivity matrix and a smoothedcomputed covariance is presented.