Abstract
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.
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Communicated by R. E. Kalaba
This work represents the results of research carried out at the Jet Propulsion Laboratory, California Institute of Technology, Pasadena, California, under NASA Contract No. NAS 7-100.
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Bierman, G.J. The treatment of bias in the square-root information filter/smoother. J Optim Theory Appl 16, 165–178 (1975). https://doi.org/10.1007/BF00935630
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DOI: https://doi.org/10.1007/BF00935630