Source localization based on particle swarm optimization for wireless sensor network

In this paper, a particle swarm optimization approach for the energy-based acoustic source localization of a wireless sensor network is presented. For this work, it is assumed that there is one acoustic source with unknown localizations which transmit acoustic signals that can be received by the nodes. The only available information to the system is the received signal energy which is not very accurate in general because of the attenuation in the process of propagation. To obtain better estimated localization of the acoustic source, maximum likelihood method is applied to transform it into extremal function, the particle swarm optimization scheme searches the optimal solution. Experimental results show that the proposed approach has the advantages of higher precision and lower computational complexity.