Toward Efficient Quality of Information Estimation in Simultaneous Acoustic Tracking and Classification of Multiple Targets

Abstract

An individual sensor's information output is often insufficient for an application, with ambiguities that require refinement or corroboration by fusion with information from other sensors. Fusion of multiple information sources is performed to create an information product of higher quality of information (QoI) that supports more effective intelligence, surveillance, and reconnaissance (ISR). In this paper we present an approach to determining the QoI attributes (metadata) relevant to tracking and classification of multiple vehicles and the necessary weighting (qualifying) terms, as information derived from multiple acoustic sensors is fused. Field trial data is used to validate the conclusions.

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Document Details

Document Type
Technical Report
Publication Date
Jul 01, 2009
Accession Number
ADA533092

Entities

People

  • David J. Thornley
  • Duncan F. Gillies
  • Ed Gentle
  • Thyagaraju Damarla

Organizations

  • United States Army Research Laboratory

Tags

Communities of Interest

  • C4I
  • Materials and Manufacturing Processes
  • Sensors

DTIC Thesaurus Topics

  • Accuracy
  • Acoustic Detectors
  • Acoustic Signals
  • Acoustic Tracking
  • Classification
  • Computational Complexity
  • Detectors
  • Estimators
  • Frequency
  • Information Science
  • Kalman Filters
  • Multiple Targets
  • Probability
  • Sensor Networks
  • Signal Processing
  • Targets
  • Tracked Vehicles

Readers

  • Regression Analysis.
  • Sensor Fusion and Tracking Systems.