Variable Order Filters

Abstract

The theory of variable order filters was derived from the author's previous studies on the application of polynomial splines and generalized splines to statistical filter theory. The current algorithms for the variable order filters are applications of and extensions of the spline function concepts. This class of filters have application to smoothing and prediction of sampled data systems for the following classes of state estimation problems: Estimation of the state vector of a linear dynamic system with rapidly changing trajectories as, for example, a maneuvering vehicle; High precision estimation of the state vector based on long observational intervals where the estimation accuracy may be limited by modelling errors; and, Estimation of the state vector when certain components of the state vector are subject to intermittent discontinuous changes as, for example, staging rockets.

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Document Details

Document Type
Technical Report
Publication Date
Dec 01, 1971
Accession Number
AD0751124

Entities

People

  • Marvin Blum

Organizations

  • Institute for Defense Analyses

Tags

Communities of Interest

  • Weapons Technologies

DTIC Thesaurus Topics

  • Accuracy
  • Algorithms
  • Coefficients
  • Computer Science
  • Curve Fitting
  • Data Sets
  • Detectors
  • Differential Equations
  • Equations
  • Kalman Filters
  • Linear Differential Equations
  • Measurement
  • Paper
  • Polynomials
  • Random Variables
  • Step Functions
  • Stochastic Processes

Fields of Study

  • Engineering

Readers

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