Optimal and Suboptimal Results in Full and Reduced Order Linear Filtering.

Abstract

This paper considers the synthesis of linear reduced order filters and the synthesis of linear full order filters with minimum complexity. The objective of a reduced order filter is to estimate a linear transformation of the state vector with a filter of lower dimension. This type of filter occurs frequently in applications. Several cases are studied. In a number of cases it is shown that singular arcs exist. In instances where certain filter parameters are not subject to optimization, it is shown that the remaining parameters can be optimized with a relatively simple procedure. Closed form solutions for a number of cases have been obtained. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Dec 01, 1976
Accession Number
ADA034398

Entities

People

  • Craig S. Sims
  • Robert B. Asher

Organizations

  • United States Air Force Academy

Tags

Communities of Interest

  • Air Platforms
  • C4I
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Algorithms
  • Applied Mathematics
  • Boundaries
  • Boundary Value Problems
  • Colorado
  • Computations
  • Differential Equations
  • Electrical Engineering
  • Equations
  • Errors
  • Filters
  • Filtration
  • Kalman Filters
  • Linear Filtering
  • Mathematical Filters
  • Riccati Equation
  • Vehicles

Fields of Study

  • Engineering

Readers

  • Control Systems Engineering.
  • Microwave Engineering.
  • Statistical inference.