Multi-Stage Data Fusion in Security and Defence

Abstract

The fundamental problem of target tracking is to estimate the state of one or more objects that persist over time, based on noisy measurements contained in a vast quantity of mostly spurious measurement data. Target tracking is closely related to a number of basic problems in statistical modelling and information extraction from noisy data. Multi-stage processing provides a wealth of processing options that can be exploited to achieve robust and high-performance surveillance. This manuscript describes a number of multi-stage tracking architectures that the author has recently studied. Additionally, we study the target cardinality problem.

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Document Details

Document Type
Technical Report
Publication Date
May 01, 2010
Accession Number
ADA581917

Entities

People

  • Stefano Coraluppi

Organizations

  • Centre for Maritime Research and Experimentation

Tags

Communities of Interest

  • Materials and Manufacturing Processes
  • Sensors

DTIC Thesaurus Topics

  • Algorithms
  • Computations
  • Data Association
  • Data Fusion
  • Detection
  • Detectors
  • Estimators
  • False Alarms
  • Measurement
  • Multiple Hypothesis Tracking
  • Multitarget Tracking
  • Probability
  • Probability Distributions
  • Radar
  • Sensor Networks
  • Surveillance
  • Target Tracking

Fields of Study

  • Computer science

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Theoretical Analysis.

Technology Areas

  • AI & ML
  • AI & ML - Machine Learning Algorithms