Robust maximum likelihood acoustic source localization in wireless sensor networks

Yong Liu, Yu Hen Hu, Quan Pan

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

9 Scopus citations

Abstract

Sensor measurements in a wireless sensor network (WSN) may significantly deviate from a commonly used Gaussian noise model due to harsh operating conditions, unreliable wireless communication links, or sensor failures. In this work, a mixed Gaussian and impulse noise model is proposed to more accurately model these types of non-Gaussian noise. However, existing maximum likelihood (ML) acoustic energy based source localization algorithms are very sensitive to non-Gaussian noise perturbations. To mitigate this shortcoming, a novel M-estimate based robust estimation formulation is derived. Extensive simulation results demonstrated superior and consistent performance advantage of this robust estimation approach compared to conventional ML estimates over a wide range of practical scenarios.

Original languageEnglish
Title of host publicationGLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference
DOIs
StatePublished - 2009
Event2009 IEEE Global Telecommunications Conference, GLOBECOM 2009 - Honolulu, HI, United States
Duration: 30 Nov 20094 Dec 2009

Publication series

NameGLOBECOM - IEEE Global Telecommunications Conference

Conference

Conference2009 IEEE Global Telecommunications Conference, GLOBECOM 2009
Country/TerritoryUnited States
CityHonolulu, HI
Period30/11/094/12/09

Keywords

  • Acoustic energy
  • M-estimate
  • Maximum likelihood
  • Robust statistics
  • Sensor network
  • Source localization
  • Target tracking

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