Title :
Linear smoothing for discrete-time systems in the presence of correlated disturbances and uncertain observations
Author :
Carazo, A. Hermoso ; Pérez, J. Linares
Author_Institution :
Dept. de Estadistica e Investigacion, Granada Univ., Spain
fDate :
8/1/1995 12:00:00 AM
Abstract :
This paper considers the smoother with the least mean-squared error (LMSE) within the class of linear smoothers for discrete linear systems whose observations may contain noise alone and the probability of this occurring is known (systems with uncertain observations). Also, we assume that state and measurement noises are correlated. The present results, together with Hermoso-Linares´s results on prediction and filtering, give a complete treatment of the LMSE linear estimation problem for such systems
Keywords :
discrete time systems; error statistics; least mean squares methods; linear systems; prediction theory; probability; smoothing methods; uncertain systems; Hermoso-Linares approach; correlated disturbances; discrete-time systems; filtering; least mean-squared error; linear smoothing; linear systems; measurement noise; prediction; probability; state noise; uncertain observations; Equations; Linear systems; Noise measurement; Nonlinear filters; Random variables; Recursive estimation; Smoothing methods; State estimation; Vectors; White noise;
Journal_Title :
Automatic Control, IEEE Transactions on
