Analytical Techniques for Tracking Filter Implementation

Abstract

This study addresses these two fundamental shortcomings to currently employed tracking filters. First, a nonlinear analysis is presented. In this analysis, a tracking filter that incorporates aircraft orientation in both the system model and measurements is compared to a tracker that uses only standard radar measurements. The addition of the orientation information enhances the tracking filter performance because, in general, aircraft orientation is strongly correlated with the acceleration of the aircraft. Improved position estimation and prediction is demonstrated with the tracking filter that incorporates orientation information. The second fundamental cause of tracking filter errors (i.e. unknown system inputs) is investigated using linear analysis techniques. First, an analysis technique is developed using frequency and time domain methodologies for determining tracking filter gains for a system with unknown exogenous inputs. An analysis technique is also developed to determine the difference in tracking filter error covariance histories using variable structure models.

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Document Details

Document Type
Technical Report
Publication Date
Dec 01, 1988
Accession Number
ADA217458

Entities

People

  • Daniel Gleason

Organizations

  • Air Force Institute of Technology

Tags

Communities of Interest

  • Air Platforms
  • C4I
  • Ground and Sea Platforms
  • Materials and Manufacturing Processes
  • Weapons Technologies

DTIC Thesaurus Topics

  • Air Force
  • Aircrafts
  • Computational Science
  • Computer Simulations
  • Control Systems
  • Detectors
  • Difference Equations
  • Differential Equations
  • Fighter Aircraft
  • Filtration
  • Fixed Wing Aircraft
  • Kalman Filters
  • Mathematical Filters
  • Random Variables
  • Stochastic Processes
  • Systems Engineering
  • Three Dimensional

Fields of Study

  • Engineering

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Control Systems Engineering.