Title :
Optimal filtering in stochastic discrete-time systems with unknown inputs
Author :
Borisov, A.V. ; Pankov, A.R.
Author_Institution :
Dept. of Appl. Math., Moscow State Aviation Inst., Russia
fDate :
12/1/1994 12:00:00 AM
Abstract :
In this note we derive a recursive filtering algorithm for the linear discrete-time dynamic system with indeterminate-stochastic inputs. The algorithm is based on the minimax-optimal method of parameter estimation in the linear regression model with parameters of two different types: unknown and stochastic with partially known characteristics
Keywords :
discrete time systems; filtering theory; minimax techniques; parameter estimation; recursive filters; statistical analysis; stochastic systems; indeterminate-stochastic inputs; linear discrete-time dynamic system; linear regression model; minimax-optimal method; optimal filtering; parameter estimation; partially known characteristics; recursive filtering algorithm; stochastic discrete-time systems; stochastic parameters; unknown inputs; unknown parameters; Covariance matrix; Filtering algorithms; Linear regression; Minimax techniques; Parameter estimation; State estimation; Stochastic processes; Stochastic systems; Symmetric matrices; Vectors;
Journal_Title :
Automatic Control, IEEE Transactions on
