Since the existing target orientation estimation methods for laser radars are not robust to the occlusion, a novel 3D orientation estimation method was proposed. The principles of the existing methods and the intrinsic characters of the surface structures for ground targets were analyzed carefully, then the feature of Projection Density Entropy (PDE) was introduced, and the relationship between PDE and target orientation was analyzed. Finally, a 3D orientation estimation method was formulated by iteratively rotating and projecting the target point cloud onto the coordinate planes together with PDE calculation. Comparative experiments were performed on the dataset containing point clouds of 25 ground targets, the performance in self-occlusion, occlusion and the noise were investigated, and the parameter tuning was discussed. The results show that the estimation error of this method is below 3° in self-occlusion, and also no more than 10 ° even in 80% occlusion. It is clear that the proposed method is robust to occlusion and converges quickly, thus is capable of estimating the 3D orientation of ladar targets in complex scenes.