Optimum Linear Redundant Measurements.
Abstract
When the measurement of a select set of system states or outputs is disturbed by additive noise of the measuring instruments, the choice of a redundant set of measurements linearly related to the originally selected set may prove useful in reducing the measurement error. The report presents theorems which establish the minimum mean-square estimate in terms of the Penrose-Moore generalized inverse. The approach taken produces the insight that the optimum estimator is error-wise equivalent to an estimator calculated on the basis of a reduction of the measurement covariance matrix S to one whose dimension equals the rank of S; that is, the estimate projects the measurement vector into a maximally dimensioned space of linearly independent coordinates. (Author)
Document Details
- Document Type
- Technical Report
- Publication Date
- Nov 01, 1970
- Accession Number
- AD0717631
Entities
People
- Sidney Berkowitz