The backscattered signals of objects under spinning motion or with rotating parts provide very rich information that can be used for classification tasks, parameter extraction, etc. Obtaining such information from noncooperative objects with an unknown target-aspect is often a complicated task with a monostatic configuration. A multistatic radar on the other hand, can exploit the spatial diversity to extract the information from the time–frequency representations obtained from multiple aspect-angles. In this paper, we propose a tomographic approach for characterizing spinning objects in terms of their shape, size, and rotation parameters using a narrow-band multistatic radar. A two-dimensional image is reconstructed after a full rotation period using tomographic methods that allows not only to estimate the shape of the target but also the rotation parameters and the dimensions of the object. This is done very efficiently by combining the tomographic images from different aspect-angles on the transformed log-polar space, instead of the time–frequency representations. Simulations and measurements were conducted for the proof of concept. The measurement results with a simple target and a continuous wave K-band radar show errors below 3$^{\circ }$ for the orientation estimation and below 5% for the estimation of the object's diameter.

中文翻译：

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用多方面散射信号的层析重建表征旋转物体

旋转运动或带有旋转部件的物体的反向散射信号提供了非常丰富的信息，可用于分类任务、参数提取等。 从具有未知目标方面的非合作物体中获取此类信息通常是具有单站配置的复杂任务. 另一方面，多基地雷达可以利用空间多样性从多方位角获得的时频表示中提取信息。在本文中，我们提出了一种使用窄带多基地雷达根据旋转物体的形状、大小和旋转参数来表征旋转物体的层析成像方法。使用断层扫描方法在完整旋转周期后重建二维图像，该方法不仅可以估计目标的形状，还可以估计旋转参数和对象的尺寸。这是通过在转换后的对数极坐标空间上组合来自不同纵角的断层图像而不是时频表示来非常有效地完成的。为概念验证进行了模拟和测量。使用简单目标和连续波 K 波段雷达的测量结果显示，方向估计误差低于 3$^{\circ }$，目标直径估计误差低于 5%。而不是时频表示。为概念验证进行了模拟和测量。使用简单目标和连续波 K 波段雷达的测量结果显示，方向估计误差低于 3$^{\circ }$，目标直径估计误差低于 5%。而不是时频表示。为概念验证进行了模拟和测量。使用简单目标和连续波 K 波段雷达的测量结果显示，方向估计误差低于 3$^{\circ }$，目标直径估计误差低于 5%。