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Signal processing by particle filtering for binary sensor networks

  • Stony Brook University

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

51 Scopus citations

Abstract

In a wireless sensor network, limited power, communication, and computational resources are the major constraints that one has to overcome in their successful deployment and utilization. Binary sensor networks are a class of networks that get around these constraints. There, the sensors transmit only a binary digit on the occurrence of the event of interest, and therefore, the signals that reach the fusion center of these networks are highly compressed and pose challenging problems for recovering the sensed information. In this paper we consider the problem of tracking a vehicle, which moves along a 2-dimensional space, by using a binary sensor network that fuses information by particle filtering.

Original languageEnglish
Title of host publication2004 IEEE 11th Digital Signal Processing Workshop and 2nd IEEE Signal Processing Education Workshop
Pages263-267
Number of pages5
StatePublished - 2004
Event2004 IEEE 11th Digital Signal Processing Workshop and 2nd IEEE Signal Processing Education Workshop - Taos Ski Valley, NM, United States
Duration: Aug 1 2004Aug 4 2004

Publication series

Name2004 IEEE 11th Digital Signal Processing Workshop and 2nd IEEE Signal Processing Education Workshop

Conference

Conference2004 IEEE 11th Digital Signal Processing Workshop and 2nd IEEE Signal Processing Education Workshop
Country/TerritoryUnited States
CityTaos Ski Valley, NM
Period08/1/0408/4/04

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