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Tracking with particle filtering in tertiary wireless sensor networks

  • Stony Brook University

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

25 Scopus citations

Abstract

Recent advances of wireless sensor networks have presented some very interesting problems for signal processing. For practical reasons, many networks are composed of simple sensors that use very little power and do not consume much communication bandwidth. A class of sensors that satisfy these requirements are the tertiary sensors. They report an approaching event with one signal and a receding event with another signal. When the event is out of their range, they do not report anything. In this paper, we apply particle filtering for processing signals from tertiary sensor networks with the purpose of tracking events (targets) within the field of the sensor network. We present an algorithm for tracking and demonstrate its performance by computer simulations.

Original languageEnglish
Title of host publication2005 IEEE ICASSP '05 - Proc. - Design and Implementation of Signal Proces.Syst.,Indust. Technol. Track,Machine Learning for Signal Proces. Signal Proces. Education, Spec. Sessions
PublisherInstitute of Electrical and Electronics Engineers Inc.
PagesIV757-IV760
ISBN (Print)0780388747, 9780780388741
DOIs
StatePublished - 2005
Event2005 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP '05 - Philadelphia, PA, United States
Duration: Mar 18 2005Mar 23 2005

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
VolumeIV

Conference

Conference2005 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP '05
Country/TerritoryUnited States
CityPhiladelphia, PA
Period03/18/0503/23/05

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