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

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