A novel PSO based acoustic source localization algorithm in Wireless Sensor Network

Yong Liu, Wen Tian Zhou, Liang Yan, Quan Pan, Yong Mei Cheng

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

3 Scopus citations

Abstract

Acoustic source localization is a very important Wireless Sensor Network (WSN) surveillance task. In real-world implementations, the localization algorithm, which is essentially an optimization of a certain cost function involving all received sensor observations, must be feasible under stringent communication, computation and energy constrains. In this paper, we propose a novel light-weight dynamic population Particle Swarm Optimization (PSO) based method to search the Maximum Likelihood Estimate (MLE) solution for the source location, reducing computation complexity as well as mitigating the affects of local optimum solutions. Moreover, instead of raw data, only signal energy observations are transmitted to the fusion center, such that bandwidth and energy consumptions can be largely decreased. The results of extensive simulations have shown the superior performance of our method in various scenarios.

Original languageEnglish
Title of host publication2010 8th World Congress on Intelligent Control and Automation, WCICA 2010
Pages820-825
Number of pages6
DOIs
StatePublished - 2010
Event2010 8th World Congress on Intelligent Control and Automation, WCICA 2010 - Jinan, China
Duration: 7 Jul 20109 Jul 2010

Publication series

NameProceedings of the World Congress on Intelligent Control and Automation (WCICA)

Conference

Conference2010 8th World Congress on Intelligent Control and Automation, WCICA 2010
Country/TerritoryChina
CityJinan
Period7/07/109/07/10

Keywords

  • Acoustic
  • Particle Swarm Optimization
  • Source localization
  • Wireless Sensor Network

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