A Two-Step Bilinear Filtering Approximation,

Abstract

A new approximation technique to a certain class of nonlinear filtering (signal processing) problems is considered here. The method is based on an approximation of a nonlinear, partially observable system by a bilinear model with fully observable states. The filter development proceeds from the assumption that the unobservable states are conditionally Gaussian with respect to the observation initially. The method is shown to be promising for real-time communication and sonar applications as demonstrated by computer simulations. Moreover, some of the traditional techniques evolve as special cases of this methodology.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1984
Accession Number
ADA138350

Entities

People

  • R. R. Mohler
  • T. U. Halawani
  • W. J. Kolodziej

Organizations

  • Oregon State University

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Accuracy
  • Algorithms
  • Differential Equations
  • Digital Computers
  • Equations
  • Filters
  • Filtration
  • Kalman Filters
  • Mathematical Filters
  • Measurement
  • Military Research
  • Nonlinear Systems
  • Partial Differential Equations
  • Random Variables
  • Simulations
  • Stochastic Control
  • Stochastic Processes

Readers

  • Calculus or Mathematical Analysis
  • Neural Network Machine Learning.
  • Radar Systems Engineering.