Ladar has became a hot research topic in target recognition community for its ability to capture the object′s explicit 3D shape. To avoid the heavy computation burden faced by the traditional recognition methods, a fast ladar target recognition method is proposed. Adopting the coarse-to-fine strategy, the models are quickly pre-screened by using the proposed orthogonal projection contour features (PCF). Then the target is registered with the hypothesis models precisely by using the iterative closest point (ICP) method. Finally, the similarities between the target and models are calculated by integrating the features matching and points matching results. Therefore, the target is recognized to the model who owes the highest similarity. The experiments are performed using the point-clouds of 25 ground targets under 96 different viewing angles. The results show that the proposed method outperforms the existing methods greatly in the term of computation efficiency, and it is very robust to orientation error and occlusion. Thus, this method is the state-of-the-art and have a high application potential.