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Localization of an unmanned ground vehicle (UGV) is a very important task for autonomous vehicle navigation. In this paper, we propose a computer vision technique to identify the location of an outdoor UGV. The proposed technique is based on 3D registration of 360 degree laser range data to a digital surface model (DSM). A long sequence of range frames is obtained from a rotating range sensor which is mounted on the top of the vehicle. Two novel approaches are proposed for accurate 3D registration of range data and the DSM. First, registration is done between range frames in a pair-wise manner followed by a refinement with the DSM. Second, we divide the DSM to several layers and find correspondences near the current vehicle elevation. This reduces the number of outliers and facilitates fast localization. Experimental results show that the proposed approaches yield better performance in 3D localization compared to conventional 3D registration techniques. Error analysis on four outdoor paths is presented with respect to ground truth.