Fast communication: Force-directed hybrid PSO-SNTO algorithm for acoustic source localization in sensor networks

Authors:
Zhijun Yu;Jianming Wei;Haitao Liu
Affiliations:
Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Science, No. 865, Changning Road, Changning Distribute, Shanghai 200050, China;Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Science, No. 865, Changning Road, Changning Distribute, Shanghai 200050, China;Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Science, No. 865, Changning Road, Changning Distribute, Shanghai 200050, China
Venue:
Signal Processing
Year:
2009

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Abstract

As a smart combination of particle swarm optimization (PSO) and sequential number-theoretic optimization (SNTO), a new hybrid PSO-SNTO algorithm is proposed to handle the initialization dependence of basic PSO algorithm. We then apply the hybrid algorithm to the acoustic source localization problem in sensor networks, which is modeled as a maximum likelihood estimation problem. Furthermore, a heuristic method based on virtual force is used to direct the particles of PSO to the global optimum, which can efficiently speed up the algorithm convergence. Simulation results demonstrate that the hybrid algorithm can achieve robust convergence with sophisticated estimation performance, and the convergence rate can be largely enhanced with the assistance of the force-directed heuristics.