Decentralized robust acoustic source localization with wireless sensor networks for heavy-tail distributed observations

Yong Liu, Yu Hen Hu, Quan Pan

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

2 Scopus citations

Abstract

In this work, an energy based acoustic source localization task in a wireless sensor network (WSN) is considered. Based on data gathered from field experiments, it is revealed that the acoustic energy gathered at sensor nodes exhibits a heavy-tail, non-Gaussian characteristic and should be fitted into a contaminated Gaussian model. This property renders conventional least square and maximum likelihood based location estimation methods ineffective. Leveraging the distributed, in-network processing nature of a WSN, a novel de-centralized robust acoustic source localization (DRASL) algorithm is proposed. With the DRASL, local sensor nodes receive sensor readings broadcast from neighboring sensors and independently compute local location estimates using a light-weight Iterative Nonlinear Reweighted Least Square (INRLS) algorithm. The local location estimate then will be relayed to a fusion center where the final location estimate is obtained as a weighted average of the local estimates. The potential advantage of this algorithm is validated using extensive simulation in a real-world operation scenario. It is show that its performance is superior than existing methods while promising to be more energy efficient.

Original languageEnglish
Title of host publication2010 IEEE Global Telecommunications Conference, GLOBECOM 2010
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Print)9781424456383
DOIs
StatePublished - 2010
Event53rd IEEE Global Communications Conference, GLOBECOM 2010 - Miami, United States
Duration: 6 Dec 201010 Dec 2010

Publication series

NameGLOBECOM - IEEE Global Telecommunications Conference

Conference

Conference53rd IEEE Global Communications Conference, GLOBECOM 2010
Country/TerritoryUnited States
CityMiami
Period6/12/1010/12/10

Keywords

  • Acoustic energy
  • Decentralized localization
  • Impulsive noise
  • M-estimate
  • Robustness
  • Wireless sensor networks

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