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