The Utilization of Data Measurement Residuals for Adaptive Kalman Filtering

Abstract

In recent years, the Kalman filter has been used extensively for passive target motion analysis (TMA) -- an application in which filter divergence is a common problem. Available methods for eliminating divergence ultimately involve increasing filter sensitivity by discounting the influence of past data. However, this procedure makes the filter more susceptible to random errors; therefore, to avoid unnecessary sacrificing of noise performance, adaptive control is required. In this report, the Kalman filter equations are derived and the associated data measurement residuals are examined to determine their suitability for providing adaptive control. An important relationship between the system performance index and the data residuals is established.

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Document Details

Document Type
Technical Report
Publication Date
Feb 08, 1974
Accession Number
AD0776218

Entities

People

  • John S. Davis
  • Vincent J. Aidala

Organizations

  • Naval Underwater Systems Center

Tags

Communities of Interest

  • Ground and Sea Platforms

DTIC Thesaurus Topics

  • Algorithms
  • Boundaries
  • Boundary Value Problems
  • Computations
  • Covariance
  • Difference Equations
  • Equations
  • Filters
  • Filtration
  • Geometry
  • Kalman Filtering
  • Kalman Filters
  • Maneuvers
  • Measurement
  • Rhode Island
  • Simulations
  • Statistics

Readers

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