Multisensor Tracking of a Maneuvering Target in Clutter with Asychronous Measurements using IMMPDA Filtering and Parallel Detection Fusion

Abstract

We present a (suboptimal) filtering algorithm for tracking a highly maneuvering target in a cluttered environment using multiple sensors dealing with possibly asynchronous (time delayed) measurements. The filtering algorithm is developed by applying the basic Interacting Multiple Model (IMM) approach, the Probabilistic Data Association (PDA) technique, and asynchronous measurement updating for state-augmented system estimation for the target. A state augmented approach is developed to estimate the time delay between local and remote sensors. A multi- sensor probabilistic data association filter is developed for parallel sensor processing for target tracking under clutter. The algorithm is illustrated via a highly maneuvering target tracking simulation example where two sensors, a radar and an infrared sensor, are used. Compared with an existing IMMPDA filtering algorithm with the assumption of synchronous (no delay) measurements sensor processing, the proposed algorithm achieves considerable improvement (especially in the case of larger delays) in the accuracy of track estimation.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Sep 09, 2003
Accession Number
ADA417405

Entities

People

  • Jitendra K. Tugnait
  • Soonho Jeong

Organizations

  • Auburn University

Tags

Communities of Interest

  • Sensors

DTIC Thesaurus Topics

  • Algorithms
  • Cartesian Coordinates
  • Covariance
  • Data Association
  • Data Fusion
  • Data Science
  • Detection
  • Detectors
  • Equations Of State
  • Errors
  • Information Science
  • Measurement
  • Probability
  • Random Variables
  • Remote Detectors
  • Simulations
  • Target Tracking

Fields of Study

  • Engineering

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Sensor Fusion and Tracking Systems.