Title :
Partitioned linear estimation algorithms: Discrete case
Author :
Lainiotis, Demetrios G.
Author_Institution :
State University of New York at Buffalo, Buffalo, New York, USA
fDate :
4/1/1975 12:00:00 AM
Abstract :
Using the "partitioning" approach to estimation, fundamentally new, robust, computationally effective and fast filtering and smoothing algorithms have been obtained. The new algorithms are given in explicit expressions of a partitioned nature in terms of decoupled forward filters. The "patitioned" algorithms are especially advantageous both from a computational as well as an analysis standpoint. They are the natural framework for studying observability, controllability, unbiasedness, and especially in deriving robust, fast, and effective numerical algorithms for Riccati equations.
Keywords :
Linear systems, stochastic discrete-time; Smoothing methods; State estimation; Algorithm design and analysis; Controllability; Filtering algorithms; Filters; Observability; Partitioning algorithms; Riccati equations; Robust control; Robustness; Smoothing methods;
Journal_Title :
Automatic Control, IEEE Transactions on
DOI :
10.1109/TAC.1975.1100907