A General Theory of Signal Integration for Fault Tolerant Distributed Sensor Networks

Abstract

The computational issues relating to information integration by multisensor systems and distributed sensor networks are an area of intense ongoing research. Many significant advances have been made recently in the field of sensor integration. This interest in Distributed Sensor Networks (DSNs) technology for information gathering is at least partially due to: (a) the development of new technology making DSNs economically feasible to implement and (b) the growing complexity of information gathering applications. The extraction and fusion of accurate information from the noisy and faulty signals returned by many sensors requires the resolution of many problems including: (a) the architecture of fault-tolerant and robust distributed sensor networks, (b) the reliable synchronization of sensor signals, (c) the efficient integration of information in order to minimize communications and processing overhead, and (d) the development of efficient computational tools for abstract representation and integration of sensor data. The sensor fusion process is of interest for the process of human decision making as well as for its applications within automated systems.

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Document Details

Document Type
Technical Report
Publication Date
Sep 30, 1994
Accession Number
ADA284825

Entities

People

  • Brandon A. Jones
  • Sundaraja Sitharama Iyengar

Organizations

  • Louisiana State University

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Algorithms
  • Artificial Intelligence
  • Change Detection
  • Computational Complexity
  • Computer Science
  • Detection
  • Detectors
  • Image Processing
  • Mathematics
  • Networks
  • Nonlinear Systems
  • Parallel Computing
  • Pattern Recognition
  • Sensor Fusion
  • Sensor Networks
  • Signal Processing
  • Wireless Sensor Networks

Fields of Study

  • Computer science
  • Engineering

Readers

  • Computer Networking
  • Systems Analysis and Design
  • Team-Based Human-Centered Cognitive Task Decision Making and Information Performance.