New smoothing algorithms based on reversed-time lumped models
Gagandeep Kaur Sidhu, U.B. Desai · IEEE Transactions on Automatic Control · 1976
Corresponding to a processx(.)with a known state model propagating in growing time, we obtain a processx_{r}(.), statistically equivalent tox(.)up to second-order properties but with a state model propagating in reversed time. This result is exploited to obtain recursive linear least-squares estimation algorithms that evolve backwards in time. The reversed-time model is shown to be closely related to the system adjoint of the original state model. Some operator-theoretic consequences are also noted.