Tracking of Multiple Maneuvering Targets in Clutter Using Multiple Sensors, IMM and JPDA Coupled Filtering

Abstract

We consider the problem of tracking multiple maneuvering targets in clutter using switching multiple target motion models. A novel suboptimal filtering algorithm is developed by applying the basic interacting multiple model (IMM) approach, the joint probabilistic data association (JPDA) technique and coupled target state estimation to a Markovian switching system. The algorithm is illustrated via a simulation example involving tracking of two highly maneuvering, at times closely spaced, targets.

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Document Details

Document Type
Technical Report
Publication Date
Jun 01, 2003
Accession Number
ADA417569

Entities

People

  • Jitendra K. Tugnait

Organizations

  • Auburn University

Tags

Communities of Interest

  • Sensors

DTIC Thesaurus Topics

  • Algorithms
  • Bayesian Networks
  • Cartesian Coordinates
  • Computational Complexity
  • Computational Science
  • Data Association
  • Detection
  • Detectors
  • Equations
  • Filtration
  • Measurement
  • Multiple Targets
  • Multitarget Tracking
  • Probability
  • Random Variables
  • Simulations
  • Target Tracking

Fields of Study

  • Engineering

Readers

  • Mathematical Modeling and Probability Theory.
  • Radar Systems Engineering.
  • Robotics and Automation.

Technology Areas

  • Space
  • Space - Space Objects
  • Space - Spacecraft Maneuvers