Abstract: To solve the problem of the declined performance of conventional maximum likelihood method in locating multiple nearfield sources in the context of nonuniform spatial noise, the nearfield signal model based on planar sensor array was firstly constructed and then the maximum likelihood localization method was derived in details to obtain the values of the azimuth and distance of sound sources. Moreover, the ant colony optimization algorithm for continuous space(ACOCS) was employed to further reduce the high computational complexity incurred in the multidimensional search process of the deduced maximum likelihood localization method. Simulations were conducted to validate the feasibility and efficiency of the proposed method. Simulation results showed that the proposed method has a higher estimation accuracy than the conventional maximum likelihood method under the lower mean squared error of both azimuth estimation and distance estimation, and can approach their respective Cramer-Rao Bound(CRB) at high signal-to-noise ratio(SNR)