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Improving Localization in Geosensor Networks through Use of Sensor Measurement Data

  • Frank Reichenbach
  • Alexander Born
  • Edward Nash
  • Christoph Strehlow
  • Dirk Timmermann
  • Ralf Bill
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5266)

Abstract

The determination of a precise position in geosensor networks requires the use of measurements which are inherently inaccurate while minimizing the required computations. The imprecise positions produced using these inaccurate measurements mean that available methods for measurement of distances or angles are unsuitable for use in most applications. In this paper we present a new approach, the Anomaly Correction in Localization (ACL) algorithm, whereby classical trilateration is combined with the measurements of physical parameters at the sensor nodes to improve the precision of the localization.

Simulation results show that for localization using triangulation of distance measurements with a standard deviation of 10% then the improvement in precision of the estimated location when using ACL is up to 30%. For a standard deviation in the measurements of 5% then an improvement in positioning precision of ca. 12% was achieved.

Keywords

Sensor Node Wireless Sensor Network Outlier Detection Digital Terrain Model Distance Error 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Frank Reichenbach
    • 1
  • Alexander Born
    • 2
  • Edward Nash
    • 2
  • Christoph Strehlow
    • 1
  • Dirk Timmermann
    • 1
  • Ralf Bill
    • 2
  1. 1.Institute of Applied Microelectronics and Computer EngineeringUniversity of RostockGermany
  2. 2.Institute for Management of Rural AreasUniversity of RostockGermany

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