This paper considers the problem of locating ground vehicles using their acoustic signatures recorded by unattended passive acoustic sensors. Acoustic signatures of the ground sources captured by different sensors within a cluster are used to generate direction of arrival (DoA) of the propagating wavefronts. Using the estimated DoAs of disparate distributed sensor node clusters, this paper introduced and compared several different existing target localization methods that provide the location and velocity estimates of a moving source. A robust source localization method is then proposed to account for large DoA errors and outliers which often occur in realistic settings. This method does not use any prior knowledge of the dynamical model of the moving source. The effectiveness and complexity of these methods are compared using synthesized and real acoustic signature data sets.