Title :
Approaches to adaptive filtering
Author_Institution :
Systems Control, Inc., Palo Alto, CA, USA
fDate :
10/1/1972 12:00:00 AM
Abstract :
The different methods of adaptive filtering are divided into four categories: Bayesian, maximum likelihood (ML), correlation, and covariance matching. The relationship between the methods and the difficulties associated with each method are described. New algorithms for the direct estimation of the optimal gain of a Kalman filter are given.
Keywords :
Adaptive Kalman filtering; Adaptive filters; Automatic control; Bayesian methods; Control systems; Filtering; Noise measurement; Optimal control; Statistics; Stochastic processes; Stochastic systems;
Journal_Title :
Automatic Control, IEEE Transactions on
DOI :
10.1109/TAC.1972.1100100
