StarDust: A Flexible Architecture for Passive Localization in Wireless Sensor Networks

Abstract

The problem of localization in wireless sensor networks where nodes do not use ranging hardware, remains a challenging problem, when considering the required location accuracy, energy expenditure and the duration of the localization phase. In this paper we propose a framework, called StarDust, for wireless sensor network localization based on passive optical components. In the StarDust framework, sensor nodes are equipped with optical retro-reflectors. An aerial device projects light towards the deployed sensor network, and records an image of the reflected light. An image processing algorithms developed for obtaining the locations of sensor nodes. For matching a node ID to a location we propose a constraint-based label relaxation algorithm. We propose and develop localization techniques based on four types of constraints: node color, neighbor information, deployment time for a node and deployment location for a node. We evaluate the performance of a localization system based on our framework by localizing a network of 26 sensor nodes deployed in a 120 60 ft squared area. The localization accuracy ranges from 2 ft to 5 ft while the localization time ranges from 10 milliseconds to 2 minutes.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Jan 01, 2006
Accession Number
ADA465193

Entities

People

  • John A. Stankovic
  • Pascal Vicaire
  • Radu Stoleru
  • Tian He

Organizations

  • University of Virginia

Tags

Communities of Interest

  • Sensors

DTIC Thesaurus Topics

  • Aircrafts
  • Algorithms
  • Change Detection
  • Computer Graphics
  • Computer Science
  • Detection
  • Detectors
  • Filters
  • Image Processing
  • Light Sources
  • Networks
  • Probability
  • Radar
  • Recognition
  • Sensor Networks
  • Transfer Functions
  • Wireless Sensor Networks

Fields of Study

  • Computer science

Readers

  • Neural Network Machine Learning.
  • Sensor Fusion and Tracking Systems.
  • Spectroscopy.