Sequential Monte Carlo radio-frequency tomographic tracking

Yunpeng Li, Xi Chen, Mark Coates, Bo Yang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

43 Citations (Scopus)

Abstract

Radio Frequency (RF) tomographic tracking is the process of tracking moving targets by analyzing changes of attenuation in wireless transmissions. This paper presents a novel sequential Monte Carlo (SMC) method for RF tomographic tracking of a single target using a wireless sensor network. The algorithm incorporates on-line Expectation Maximization (EM) to estimate model parameters. Based on experimental measurements, we introduce a new measurement model for the attenuation caused by a target. We assess performance through numerical simulation and demonstrate that it significantly outperforms previous RF tomographic tracking procedures.

Original languageEnglish
Title of host publication2011 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2011 - Proceedings
PublisherIEEE
Pages3976-3979
Number of pages4
ISBN (Print)9781457705397
DOIs
Publication statusPublished - 12 Jul 2011
Event36th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2011 - Prague, Czech Republic
Duration: 22 May 201127 May 2011

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
ISSN (Print)1520-6149

Conference

Conference36th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2011
CountryCzech Republic
CityPrague
Period22/05/1127/05/11

Keywords

  • On-line EM
  • RF Tomography
  • Sequential Monte Carlo
  • Wireless Sensor Networks

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

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