The maximum likelihood（ ML） localization algorithm for wireless sensor networks（ WSNs） based on acoustic source energy has strong anti-noise ability

high precision

and it is suitable for multiple targets localization at the same time; but it needs large amount of calculation and is not suitable for real-time positioning.Aiming at shortcoming of the existing algorithm

propose a maximum likelihood localization algorithm based on adaptive iteration. The new algorithm treats the cost function as objective function and search target location adaptively in given range of gradient error. Propose variable step size searching algorithm

based on Sigmoid function

in order to improve convergence speed and positioning precision. Simulation experiment result show that compared with the maximum likelihood localization algorithm

the proposed algorithm has less amount of calculation

high positioning precision

so it can meet the requirement of higher positioning precision and speed

has certain practical significance.