Fast Maximum Likelihood Localization of Near-Field Sources

Abstract

Conventional methods for locating near-field sources generally suffer performance degradation when the assumption of uniform spatial Gaussian noise does not hold. In this paper study the scenario of non-uniform spatial Gaussian noise. First we construct the near-field signal model based on planar sensor array and derive the maximum likelihood method for obtaining the azimuth and distance of sound sources, then we proposed two fast algorithms-stepwise-concentrated maximum likelihood method(SML) and approximate maximum likelihood method(AML) to reduce the high computational complexity of maximum likelihood localization method. Simulation results show that the two proposed methods outperform conventional maximum likelihood method, with lower computational complexity and less mean squared error of both azimuth estimation and distance estimation.