Polynomial Estimators for Time Discrete Systems in Hilbert Space,

Abstract

Minimum variance finite polynomial estimators are investigated for time-discrete systems. The estimation problem is formulated in Hilbert space with the optimal estimate as the projection on the linear manifold generated by a finite set of polynomials of the observer. It is shown that this estimate may be partitioned into a predictor and corrector with the corrector being expressed as the product of a weighting vector and measurement residual. The problem of updating the estimator is viewed as two separate problems: incorporating new data and changing the time of the estimate. The first requires the generation of an observation residual and corresponding weighting vector while the second is a prediction or smoothing operation. General expressions for smoothing, filtering and prediction are developed as are formulas for the generation of an orthogonal set set of measurement residuals. (Author)

Document Details

Document Type
Technical Report
Publication Date
Sep 01, 1972
Accession Number
AD0755805

Entities

People

  • Wesley K. Masenten

Organizations

  • University of California, Los Angeles

Tags

DTIC Thesaurus Topics

  • Demographic Cohorts
  • Estimators
  • Filtration
  • Hilbert Space
  • Mathematics
  • Measurement
  • Observation
  • Observers
  • Polynomials
  • Residuals

Fields of Study

  • Engineering
  • Mathematics

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Approximation Theory.

Technology Areas

  • Space