Decentralized Estimation of Linear Gaussian Systems

Abstract

In this paper, we propose a framework for the design of linear decentralized estimation schemes based on a team-theoretic approach. We view local estimates as "decisions" which affect the information received by other decision makers. Using results from team theory, we provide necessary conditions for optimality of the estimates. For fully decentralized structures, these conditions provide a complete closed-form solution of the estimation problem. The complexity of the resulting estimation algorithms is studied as a function of the performance measure, and in the context of some simple examples.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1981
Accession Number
ADA458792

Entities

People

  • David A. Castañón

Organizations

  • Massachusetts Institute of Technology

Tags

Communities of Interest

  • C4I
  • Human Systems

DTIC Thesaurus Topics

  • Abstracts
  • Algorithms
  • Command And Control
  • Command And Control Systems
  • Data Processing
  • Equations
  • Estimators
  • Hilbert Space
  • Integral Equations
  • Kalman Filters
  • Massachusetts
  • Notation
  • Observation
  • Optimal Estimators
  • Random Variables
  • Standards
  • Statistics

Fields of Study

  • Computer science
  • Engineering
  • Mathematics

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Systems Analysis and Design