In the target recognition of laser radar (ladar), the accurate estimation of target pose can effectively simplify the recognition process. To achieve 3D pose estimation of rigid objects on the ground and simplify the complexity of the algorithm, a novel pose estimation method is proposed in this paper. In this approach, based on the feature that most rigid objects on the ground have large planar areas which are horizontal on the top of the targets and vertical sides and combined with the 3D geometric characteristics of ladar range images, the planar normals of rigid targets were adopted as the vectors in the positive direction of the axes in the model coordinate system to estimate the 3D pose angles of targets. The simulation experiments were performed with six military vehicle models and the performance in self-occlusion, occlusion, and noise was investigated. The results show that the estimation errors are less than 2° in self-occlusion. For the tank LECRERC model, as long as the upper and side planes of the target are not completely occluded, even though the occlusion reaches 80%, the pose angles can be estimated with the estimation error less than 2.5°. Moreover, the proposed method is robust to noise and effective.
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