A Distributed and Energy-Efficient Framework for Neyman-Pearson Detection of Fluctuating Signals in Large-Scale Sensor Networks

Abstract

To address the challenges inherent to a problem of practical interest -- of Neyman-Pearson detection of fluctuating radar signals using wireless sensor networks, we propose in this paper a distributed and energy-efficient framework. Such framework is scalable with respect to the network size, and is able to greatly reduce the dependence on the central fusion center. It assumes a clustering infrastructure, and addresses signal processing and communications related issues arising from different layers. This framework includes a distributed scheduling protocol and a distributed routing protocol, which enable sensor nodes to make their own decisions about information transmissions, without requiring the knowledge of the network global information. In this framework, energy efficiency manifests itself at different network layers in a distributed fashion, and a balance between the detection performance and the energy efficiency is also attained.

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 2010
Accession Number
ADA559293

Entities

People

  • Brian M. Sadler
  • Rick Blum
  • Yang Yang

Organizations

  • Lehigh University

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Algorithms
  • Computing System Architectures
  • Detection
  • Detectors
  • Digital Communications
  • Energy Consumption
  • Energy Efficiency
  • False Alarms
  • Military Research
  • Probability
  • Radar Signals
  • Random Variables
  • Sensor Networks
  • Signal Detection
  • Signal Processing
  • Simulations
  • Wireless Sensor Networks

Fields of Study

  • Computer science

Readers

  • Neural Network Machine Learning.
  • Radar Systems Engineering.
  • Systems Analysis and Design