Cluster scheduling in range only tracking

Özgür Özfidan*, Hakan A. Çirpan, Uluǧ Bayazit

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

This paper presents a sensor scheduling algorithm in a classical range-only target tracking application. Since only a small portion of deployed sensors can provide useful information about the position of target at a specific time instant, clustering method is utilized and Dynamic Cluster Scheduling (DCS) is applied instead of scheduling the individual sensor nodes. Particle filtering algorithm is employed for the tracking task, by processing data provided by the sensor nodes in the active cluster Active cluster is updated at each time step by comparing the position of master node in every cluster and the estimated target position. Cramér-Rao Bound is used as a comparison criteria for the proposed scheduling method. Simulation results show that activated sensor nodes during the overall tracking task in the region of interest are quite close to the scheduling results obtained with the Posterior Cramér-Rao Bound which sets a theoretical lower limit on the estimator performance.

Original languageEnglish
Title of host publicationISSPIT 2007 - 2007 IEEE International Symposium on Signal Processing and Information Technology
Pages704-709
Number of pages6
DOIs
Publication statusPublished - 2007
EventISSPIT 2007 - 2007 IEEE International Symposium on Signal Processing and Information Technology - Cairo, Egypt
Duration: 15 Dec 200718 Dec 2007

Publication series

NameISSPIT 2007 - 2007 IEEE International Symposium on Signal Processing and Information Technology

Conference

ConferenceISSPIT 2007 - 2007 IEEE International Symposium on Signal Processing and Information Technology
Country/TerritoryEgypt
CityCairo
Period15/12/0718/12/07

Keywords

  • Particle filters
  • Sensor scheduling
  • Sequential Monte Carlo
  • Target tracking

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