Sensor Placement for Grid Coverage Under Imprecise Detections

Abstract

We present a resource-bounded optimization framework for sensor resource management under the constraints of sufficient grid coverage of the sensor field. We offer a unique "minimalistic" view of distributed sensor networks in which sensors transmit/report a minimum amount of sensed data. The proposed theory is aimed at optimizing the number of sensors and determining their placement to support such minimalistic sensor networks. We represent the sensor field as a grid (two- or three-dimensional) of points. The optimization framework is inherently probabilistic due to the uncertainty associated with sensor detections. The proposed algorithm addresses coverage optimization under constraints of imprecise detections and terrain properties. The issue of preferential coverage of grid points (based on relative measures of security and tactical importance) is also modeled. Experimental results for an example sensor field with obstacles demonstrate the application of our approach.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 2005
Accession Number
ADA440417

Entities

People

  • Krishnendu Chakrabarty
  • Santpal S. Dhillon
  • Sundaraja Sitharama Iyengar

Organizations

  • Duke University

Tags

Communities of Interest

  • Sensors

DTIC Thesaurus Topics

  • Algorithms
  • Case Studies
  • Computational Complexity
  • Computer Science
  • Data Processing
  • Deployment
  • Detection
  • Detectors
  • Networks
  • Optimization
  • Resource Management
  • Sensor Networks
  • Three Dimensional
  • Two Dimensional
  • Wireless Sensor Networks

Fields of Study

  • Computer science

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Computational Fluid Dynamics (CFD)
  • Sensor Fusion and Tracking Systems.