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3D Imaging of Rapidly Spinning Space Targets Based on a Factorization Method

机译:基于分解方法的快速旋转空间目标的3D成像

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摘要

Three-dimensional (3D) imaging of space targets can provide crucial information about the target shape and size, which are significant supports for the application of automatic target classification and recognition. In this paper, a new 3D imaging of space spinning targets via a factorization method is proposed. Firstly, after the translational compensation, the scattering centers two-dimensional (2D) range and range-rate sequence induced by the target spinning is extracted using a high resolution spectral estimation technique. Secondly, measurement data association is implemented to obtain the scattering center trajectory matrix by using a range-Doppler tracker. Then, we use an initial coarse angular velocity to generate the projection matrix, which consists of the scattering centers range and cross-range, and a factorization method is applied iteratively to the projection matrix to estimate the accurate angular velocity. Finally, we use the accurate estimate spinning angular velocity to rescale the projection matrix and the well-scaled target 3D geometry is reconstructed. Compared to the previous literature methods, ambiguity in the spatial axes can be removed by this method. Simulation results have demonstrated the effectiveness and robustness of the proposed method.
机译:空间目标的三维(3D)成像可以提供有关目标形状和大小的关键信息,这为自动目标分类和识别的应用提供了重要支持。在本文中,提出了一种新的通过分解方法对空间旋转目标进行3D成像的方法。首先,在平移补偿之后,使用高分辨率光谱估计技术提取由目标旋转引起的散射中心二维(2D)范围和范围速率序列。其次,利用距离多普勒跟踪仪实现测量数据关联以获得散射中心轨迹矩阵。然后,我们使用初始的粗角速度来生成投影矩阵,该投影矩阵由散射中心范围和交叉范围组成,并且对投影矩阵迭代应用分解法以估计准确的角速度。最后,我们使用精确的估计旋转角速度来重新缩放投影矩阵,并重建缩放比例良好的目标3D几何形状。与以前的文献方法相比,这种方法可以消除空间轴上的歧义。仿真结果证明了该方法的有效性和鲁棒性。

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