A novel distributed sensor positioning system using the dual of target tracking

Liqiang Zhang, Qiang Cheng, Yingge Wang, Sherali Zeadally

Research output: Contribution to journalArticlepeer-review

98 Scopus citations

Abstract

As one of the fundamental issues in wireless sensor networks (WSNs), the sensor localization problem has recently received extensive attention. In this work, we investigate this problem from a novel perspective by treating it as a functional dual of target tracking. In traditional tracking problems, static location-aware sensors track and predict the position and/or velocity of a moving target. As a dual, we utilize a moving location assistant (LA) (with a global positioning system (GPS) or a predefined moving path) to help location-unaware sensors to accurately discover their positions. We call our proposed system Landscape. In Landscape, an LA (an aircraft, for example) periodically broadcasts its current location (we call it a beacon) while it moves around or through a sensor field. Each sensor collects the location beacons, measures the distance between itself and the LA based on the received signal strength (RSS), and individually calculates their locations via an Unscented Kalman Filter (UKF)-based algorithm. Landscape has several features that are favorable to WSNs, such as high scalability, no intersensor communication overhead, moderate computation cost, robustness to range errors and network connectivity, etc. Extensive simulations demonstrate that Landscape is an efficient sensor positioning scheme for outdoor sensor networks.

Original languageEnglish
Pages (from-to)246-250
Number of pages5
JournalIEEE Transactions on Computers
Volume57
Issue number2
DOIs
StatePublished - Feb 2008

Bibliographical note

Funding Information:
This work is supported in part by an Indiana University Faculty Research Grant. The authors thank Dr. Y. Zhang and Dr. M. Fromherz at PARC and Dr. V. Raghavan at DARPA for providing them with the MDS-MAP codes for comparisons. They also thank Dr. Y. Shang at the University of Missouri, Columbia, for providing them with information on the MDS-MAP codes.

Keywords

  • Localization algorithm
  • Unscented Kalman Filter
  • Wireless sensor networks

ASJC Scopus subject areas

  • Software
  • Theoretical Computer Science
  • Hardware and Architecture
  • Computational Theory and Mathematics

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