Accession Number : AD0720394
Title : Adaptive Estimation Algorithms.
Descriptive Note : Technical rept.,
Corporate Author : IOWA STATE UNIV AMES ENGINEERING RESEARCH INST
Personal Author(s) : Levy,Larry J.
Report Date : DEC 1970
Pagination or Media Count : 179
Abstract : The study considers the problem of estimating the states of a linear discrete dynamical system when the covariance matrix, R, of the stationary white sequence corrupting the measurement and/or the covariance matrix, Q, of the stationary white input sequence are unknown. Two new adaptive estimators, called the Reprocessing Filter (RF) and the Maximum A Posteriori (MAP) estimator, are developed which jointly estimate the state variables and the unknown R and/or Q. The new feature common to both estimators is the use of easily implementable estimators of R and/or Q in a reprocessing configuration with the Kalman-filter algorithm. (Author)
Descriptors : (*ADAPTIVE CONTROL SYSTEMS, MATHEMATICAL MODELS), LINEAR SYSTEMS, MATRICES(MATHEMATICS), LEAST SQUARES METHOD, INFORMATION THEORY, WHITE NOISE, MULTIVARIATE ANALYSIS, ALGORITHMS, OPTIMIZATION, DECISION THEORY, THESES
Subject Categories : Statistics and Probability
Distribution Statement : APPROVED FOR PUBLIC RELEASE