Distributed Sensor System Decision Analysis Using Team Strategies.

Abstract

A distributed (or decentralized) multiple sensor system is considered under binary hypothesis environments. The system is deployed with a host sensor and multiple slave sensors. All sensors have their own independent decision makers (DM) which are capable of declaring local decisions based only on their own observation of the environment. The communication between the host sensor (HS) and the slave sensors (SS) is conditional upon the host sensor's command. Each communication that takes place involves a communication cost which plays an important role in approaches taken in this study. The conditional communication with cost initiates the team strategy in making the final decisions at the host sensor. The objectives are not only to apply the team strategy method in the decision making process, but also to minimize the expected system cost (or the probability or error in making decisions) by optimizing thresholds in the host sensor. The analytical expression of the expected system cost is numerically evaluated for Gaussian statistics over threshold locations in the host sensor to find an optimal threshold location for a given communication cost. The computer simulations of various sensor systems for Gaussian observations are also performed to understand the behavior of each system with respect to correct detections, false alarms, and target misses. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Jul 01, 1991
Accession Number
ADA240250

Entities

People

  • Dimitri Kazakos
  • Howard C. Choe

Organizations

  • University of Virginia

Tags

Communities of Interest

  • C4I
  • Materials and Manufacturing Processes
  • Sensors

DTIC Thesaurus Topics

  • Computer Programs
  • Data Fusion
  • Detection
  • Detectors
  • Electrical Engineering
  • Engineering
  • Environment
  • False Alarms
  • Information Processing
  • Observation
  • Probability
  • Probability Density Functions
  • Sensor Networks
  • Signal Processing
  • Simulations
  • Statistics
  • Warning Systems

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Sensor Fusion and Tracking Systems.
  • Systems Analysis and Design