Evolutionary Control of an Autonomous Field

Abstract

An autonomous field of sensor nodes must acquire and track targets of interest traversing the field. Small detection ranges limit the detectability of the field. As detections occur in the field, detections are transmitted acoustically to a master node. Both detection processing and acoustic communication drain a node's power source. To maximize field life, an approach must be developed to control processes carried out in the field. This paper presents an adaptive threshold control scheme that minimizes power consumption while still maintaining the field-level probability of detection. The power consumption of the field of sensor nodes is driven by the false alarm rate and target detection rate at the individual sensor nodes in this problem formulation. The control law to be developed is based on a stochastic optimization technique known as evolutionary programming. Results show that by dynamically adjusting sensor thresholds and routing structures, the controlled field will have twice the life of the fixed field.

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Document Details

Document Type
Technical Report
Publication Date
Aug 01, 2001
Accession Number
ADA434201

Entities

People

  • Barbara Dean
  • Dale M. Klamer
  • Mark W. Owen

Organizations

  • Naval Information Warfare Systems Command

Tags

Communities of Interest

  • Materials and Manufacturing Processes
  • Sensors

DTIC Thesaurus Topics

  • Acquisition
  • Algorithms
  • Data Acquisition
  • Data Fusion
  • Detection
  • Detectors
  • Electrical Engineering
  • Evolutionary Algorithms
  • False Alarms
  • Genetic Algorithms
  • Mathematics
  • Optimization
  • Probability
  • Random Variables
  • Sensor Networks
  • Target Detection
  • Warning Systems

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Plasma Physics / Magnetohydrodynamics
  • Sensor Fusion and Tracking Systems.