A sensor selection approach for target tracking in sensor networks with quantized measurements

Long Zuo, Ruixin Niu, Pramod K. Varshney

Research output: Chapter in Book/Entry/PoemConference contribution

57 Scopus citations

Abstract

This paper extends our earlier work on sensor selection [1]. We are now focusing on a more challenging problem of how to effectively utilize quantized sensor data for target tracking in sensor networks by considering sensor selection problems with quantized data. A subset of sensors are dynamically selected to optimize the tracking performance. The one-step-look-ahead posterior Cramer-Rao Lower Bound (CRLB) on the state estimation error is proposed as the sensor selection criterion. Particle filtering method is employed to compute the posterior CRLB, as well as to estimate the target state. Simulation results show that the proposed posterior CRLB based method outperforms the one based on information theoretic measures.

Original languageEnglish (US)
Title of host publication2008 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP
Pages2521-2524
Number of pages4
DOIs
StatePublished - 2008
Event2008 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP - Las Vegas, NV, United States
Duration: Mar 31 2008Apr 4 2008

Publication series

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

Other

Other2008 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP
Country/TerritoryUnited States
CityLas Vegas, NV
Period3/31/084/4/08

Keywords

  • Particle filters
  • Posterior CRLB
  • Quantization
  • Sensor networks
  • Target tracking

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

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