
Accession Number : AD0750863
Title : Estimation of the Covariance Parameters in TimeDiscrete Linear Systems with Applications to Adaptive Filtering.
Descriptive Note : Technical operating rept.,
Corporate Author : AEROSPACE CORP EL SEGUNDO CALIF ENGINEERING SCIENCE OPERATIONS
Personal Author(s) : Smith,P. L.
Report Date : 31 MAY 1971
Pagination or Media Count : 92
Abstract : The Kalman filter sequentially generates the minimum variance estimate of the state of a linear dynamic system. This estimate is a function of the covariance parameters of the dynamic system model, which implies that these be known a priori. Unfortunately some or all of these covariance parameters are often unknown in engineering applications. Two methods of estimating the unknown covariance parameters are examined in the dissertation. The first method is to compute the maximum likelihood estimates of the unknown covariance parameters from the measurement residuals generated by a suboptimal sequential filter. The second method is to estimate the states and unknown covariance parameters from the measurements simultaneously. (Author)
Descriptors : (*ADAPTIVE CONTROL SYSTEMS, MATHEMATICAL MODELS), LINEAR SYSTEMS, STOCHASTIC PROCESSES, RANDOM VARIABLES, DIFFERENCE EQUATIONS, MATRICES(MATHEMATICS), PARTIAL DIFFERENTIAL EQUATIONS, STATISTICAL ANALYSIS, OPTIMIZATION
Subject Categories : Statistics and Probability
Distribution Statement : APPROVED FOR PUBLIC RELEASE