Accession Number : AD0665883
Title : OPTIMAL FILTERING FOR GAUSS-MARKOV NOISE.
Corporate Author : AEROSPACE CORP EL SEGUNDO CALIF EL SEGUNDO TECHNICAL OPERATIONS
Personal Author(s) : Stubberud,A. R.
Report Date : DEC 1967
Pagination or Media Count : 20
Abstract : The optimal continuous-filtering problem for the case of linear dynamics, linear measurements, and gaussian white disturbance and measurement noise has been solved by Kalman and Bucy. In this study, their results are generalized for the case where measurement noise is a Gauss-Markov process, but without augmenting state, as has already been done. Proof is presented that the optimal continuous-filtering problem can be solved by simply replacing the observation vector with a derived observation vector and an initial condition. When the derived observation vector is used, colored noise is eliminated and only the standard Kalman filter problem, easily solvable, remains. (Author)
Descriptors : (*INFORMATION THEORY, CONTROL SYSTEMS), MATHEMATICAL ANALYSIS, OPTIMIZATION
Subject Categories : Cybernetics
Distribution Statement : APPROVED FOR PUBLIC RELEASE