Distributed Detection Theory and Data Fusion

Abstract

Design of distributed order statistic constant false alarm rate (OS-CFAR) detection systems with data fusion was investigated. Its performance for different fusion rules and for a variety of nonhomogeneous backgrounds such as clutter edges and interfering targets was analyzed. Issues related to sampling and quantization in distributed detection systems were addressed. Sampling schemes for signal detection based on Ali-Silvey distance measures were derive. Performance enhancement over uniform sampling was shown. A number of collaborative research projects with Rome Laboratory engineers were carried out. The most notable one was the development of a prototype of an expert system CFAR (ES-CFAR) processor. This processor intelligently selects the CFAR algorithm based upon the observed characteristics of the environment. Substantial performance improvement over a conventional CFAR processor was demonstrated. Distributed detection, Data fusion, Detection theory.

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Document Details

Document Type
Technical Report
Publication Date
Mar 01, 1994
Accession Number
ADA280410

Entities

People

  • Pramod Varshney

Organizations

  • Syracuse University

Tags

DTIC Thesaurus Topics

  • Air Force
  • Airborne Warning And Control System
  • Algorithms
  • Control Systems
  • Data Fusion
  • Detection
  • Detectors
  • Engineering
  • Expert Systems
  • False Alarms
  • Multiple Targets
  • Radar
  • Sampling
  • Sensor Fusion
  • Signal Detection
  • Signal Processing
  • Warning Systems

Fields of Study

  • Engineering

Readers

  • Distributed Systems and Data Platform Development
  • Radar Systems Engineering.