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

Content Provider	IEEE Xplore Digital Library
Author	Yong Liu Wen-tian Zhou Yan Liang Quan Pan Yong-mei Cheng
Copyright Year	2010
Description	Author affiliation: College of Automation, Northwestern Polytechnical University, Xi'an, China (Yong Liu; Wen-tian Zhou; Yan Liang; Quan Pan; Yong-mei Cheng)
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.
Starting Page	820
Ending Page	825
File Size	1028483
Page Count	6
File Format	PDF
ISBN	9781424467129
e-ISBN	9781424467129
DOI	10.1109/WCICA.2010.5554104
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-07-07
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Wireless sensor networks Maximum likelihood estimation Particle swarm optimization Automation Position measurement Surveillance Heuristic algorithms Wireless Sensor Network Acoustic Source Localization Particle Swarm Optimization
Content Type	Text
Resource Type	Article

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