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

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.