Source localization in sensor networks with Rayleigh faded signals

Ruixin Niu, Pramod K. Varshney

Research output: Chapter in Book/Entry/PoemConference contribution

8 Scopus citations

Abstract

Source localization is investigated for a sensor network with passive sensors. The signal emitted by the source endures Rayleigh fading during its propagation, and its average intensity is a function of the distance from the source. Maximum likelihood (ML) source location estimators that use the output, or its quantized version, of the non-coherent receiver is proposed. The ML estimators' Cramér-Rao lower bounds (CRLBs) are derived. Due to the fading effect, the proposed estimator's performance is degraded, compared to the ideal case without fading. However, it can still accurately estimate the source's position and intensity, and achieve its CRLB with relatively small amount of resources, namely small number of observations, sensors and quantization bits.

Original languageEnglish (US)
Title of host publication2007 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP '07
PagesIII1229-III1232
DOIs
StatePublished - 2007
Event2007 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP '07 - Honolulu, HI, United States
Duration: Apr 15 2007Apr 20 2007

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume3
ISSN (Print)1520-6149

Other

Other2007 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP '07
Country/TerritoryUnited States
CityHonolulu, HI
Period4/15/074/20/07

Keywords

  • Cramér-Rao lower bound
  • Localization
  • Quantization
  • Rayleigh fading
  • Sensor networks

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

Fingerprint

Dive into the research topics of 'Source localization in sensor networks with Rayleigh faded signals'. Together they form a unique fingerprint.

Cite this