Tracking Procedure for Non-Normally Distributed Measurement Errors.

Abstract

The Kalman Filter is a widely used procedure in tracking algorithms. When normality assumptions are violated, the Kalman Filter performance tends to degrade. In this thesis a new procedure is introduced for accommodating non-normal properties of measurement error distributions. The procedure is developed for the multi-observer situation. Simulation experiment results are presented and numerical comparisons are made between the Kalman Filter performance and that of the new procedure. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 1987
Accession Number
ADA186287

Entities

People

  • Alexander Kukliansky

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Sensors

DTIC Thesaurus Topics

  • Abstracts
  • Algorithms
  • Computations
  • Data Science
  • Equations
  • Estimators
  • Filters
  • Information Science
  • Kalman Filters
  • Measurement
  • Normality
  • Observers
  • Simulations
  • Standards
  • Statistical Algorithms
  • Statistical Analysis
  • Statistics

Readers

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