A Software Framework for Heterogeneous, Distributed Data Fusion

Abstract

In this paper we describe a software framework to enable heterogeneous, distributed data fusion of disparate information sources. The framework is agent-based and consists of three main elements. The first is a generalization of the target state to a container of arbitrary, uncertain attributes. The structure of this estimate can vary both across time and across different nodes in the same network. The second is the development of composable process and observation models. These make it possible to dynamically change the models at runtime to fit the current target state estimate.

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Document Details

Document Type
Technical Report
Publication Date
Jul 01, 2006
Accession Number
ADA498675

Entities

People

  • Joshua J. Walters
  • Simon J. Julier

Organizations

  • United States Naval Research Laboratory

Tags

Communities of Interest

  • Energy and Power Technologies
  • Materials and Manufacturing Processes
  • Sensors

DTIC Thesaurus Topics

  • Aircrafts
  • Algorithms
  • Computing System Architectures
  • Data Fusion
  • Detectors
  • Information Processing
  • Kalman Filters
  • Mathematical Models
  • Mesh Networks
  • Military Research
  • Models
  • Network Topology
  • Networks
  • Probability
  • Probability Distributions
  • Sensor Networks
  • Software Agents

Fields of Study

  • Computer science
  • Engineering

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Distributed Systems and Data Platform Development