An Analytical Framework for Soft and Hard Data Fusion: A Dempster-Shafer Belief Theoretic Approach

Abstract

The recent experiences of asymmetric urban military operations have highlighted the pressing need for incorporation of soft data, such as informant statements, into the fusion process. Soft data are fundamentally different from hard data (generated by physics-based sensors), in the sense that the information they provide tends to be qualitative and subject to interpretation. These characteristics pose a major obstacle to using existing multi-sensor data fusion frameworks, which are quite well established for hard data. Given the critical and sensitive nature of intended applications soft/hard data fusion requires a framework that allows for convenient representation of various data uncertainties common in soft/hard data, and provides fusion techniques that are robust, mathematically justifiable, and yet effective. This would allow an analyst to make decisions with a better understanding of the associated uncertainties as well as the fusion mechanism itself.

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Document Details

Document Type
Technical Report
Publication Date
Aug 01, 2012
Accession Number
ADA566246

Entities

People

  • Thanuka L Wickramarathne

Organizations

  • University of Miami

Tags

Communities of Interest

  • C4I
  • Energy and Power Technologies
  • Engineered Resilient Systems
  • Sensors
  • Weapons Technologies

DTIC Thesaurus Topics

  • Bayesian Networks
  • Command And Control
  • Communications Intelligence
  • Computational Science
  • Data Fusion
  • Detectors
  • Information Processing
  • Information Science
  • Information Systems
  • Mesh Networks
  • Multiagent Systems
  • Network Topology
  • Probabilistic Models
  • Probability
  • Probability Distributions
  • Sensor Networks
  • Signals Intelligence

Readers

  • Distributed Systems and Data Platform Development
  • Military and Counterinsurgency Studies.
  • Strategic Security Studies