基于刚体目标3维运动过程中的几何不变性，可以利用目标上多个散射点在单天线雷达1维距离像序列中的1维距离数据，重建出目标未知的3维结构和运动路径。针对此1维到3维的几何重构问题，提出了一种雷达刚体目标结构和运动的3维重建算法，该算法可利用散射点复杂的1维距离数据进行重建，并且采用非线性优化技术实现了对目标重建参数的捆绑调整(bundle adjustment)。另外，该算法中引入了目标的平移模型，使目标的平移参数能够与旋转参数一并求解，从而避免了距离对准操作的误差对重建精度的影响。仿真实验结果表明，由于重建数据中散射点的数量以及目标3维运动的丰富性得到了显著提高，尤其是最优化技术在算法中的成功应用，重建算法的鲁棒性得到了有效增强。

Based on the geometry invariance of the rigid target during its 3D motion, the targets unknown 3D shape and motion can be reconstructed using scatterers of the 1D range extracted from the range image sequence of the single-antenna radar. For this geometric reconstruction of 1D-to-3D, we propose a 3D reconstruction algorithm for the shape and motion of the radar rigid target. The reconstruction can be realized using the complex 1D range data of the scatterers and the bundle adjustment for the target's reconstructed parameters is achieved with the nonlinear optimization utilized. Furthermore, since the targets translation model is introduced in the algorithm, the translation parameters can be solved together with the rotation. Thus, the impact for the reconstructed accuracy caused by the error of the range alignment processing is weakened. The simulations verify that, due to the remarkable improvement of the scatterers quantity and the richness of the target's 3D motion in the reconstructed data and, specially, the successful application of the optimization, the robustness of the algorithm is enhanced effectively.