Resilient Localization for Sensor Networks in Outdoor Environments

Abstract

A process which computes the physical locations of nodes in a wireless sensor network is called localization. Self-localization is critical for large-scale sensor networks because manual or assisted localization is often impractical due to time requirements, economic constraints or inherent limitations of deployment scenarios. We have developed a service for reliably localizing wireless sensor networks in environments conducive to ranging errors by using a custom hardware-software solution for acoustic ranging and a family of self-localization algorithms. The ranging solution improves on previous work, extending the practical measurement range threefold "20-30m" while maintaining a distance-invariant median measurement error of about 1% of maximum range "33cm". The localization scheme is based on least squares scaling with soft constraints. Evaluation using ranging results obtained from sensor network field experiments shows that the localization scheme is resilient against large-magnitude ranging errors and sparse range measurements, both of which are common in large-scale outdoor sensor network deployments.

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Document Details

Document Type
Technical Report
Publication Date
Jun 01, 2004
Accession Number
ADA484826

Entities

People

  • Gul Agha
  • Kirill Mechitov
  • Sameer Sundresh
  • Wooyoung Kim
  • Youngmin Kwon

Organizations

  • University of Illinois Urbana–Champaign

Tags

Communities of Interest

  • Energy and Power Technologies
  • Engineered Resilient Systems
  • Sensors

DTIC Thesaurus Topics

  • Accuracy
  • Acoustic Detection
  • Acoustic Signals
  • Algorithms
  • Background Noise
  • Coordinate Systems
  • Detection
  • Detectors
  • Global Positioning Systems
  • Measurement
  • Networks
  • Range Finding
  • Reliability
  • Sensor Networks
  • Signal Detection
  • Signal Processing
  • Wireless Sensor Networks

Fields of Study

  • Computer science

Readers

  • Acoustical Oceanography.
  • Operations Research
  • Sensor Fusion and Tracking Systems.