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首页> 外文期刊>Aerospace and Electronic Systems, IEEE Transactions on >Three-dimensional precession feature extraction of space targets
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Three-dimensional precession feature extraction of space targets

机译：空间目标的三维进动特征提取

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摘要

Precession is one of the most common kinds of micro-motions for space targets. Because the precession of a target consists of the synthesis of spinning motion and coning motion, the modulation characteristics of its radar returns are more complicated than those of a simple spinning target. This makes it very difficult to extract accurate micro-motion features and structure characteristics from the object's radar returns. In this paper, based on the distributed radar networks, we present an algorithm for extracting the three-dimensional (3-D) precession features of cone-shaped space targets. This algorithm takes the advantages of the multi-view of the distributed radar networks. In the paper, we first analyze the micro-Doppler (m-D) effect on range-slow-time plane induced by precession and then present the algorithm step by step, in which some relevant problems are discussed in detail and, meanwhile, the respective simulations are given. With aid of the proposed algorithm, some 3-D precession features and structure characteristics of a target, such as the 3-D coning vector, spinning period, precession period, precession angle and the radius of the cone bottom, can be extracted accurately. The length of the target can also be estimated. In the last section of the paper, we also give the discussion of the robustness of the proposed algorithm as well as the respective simulation results.
机译：进动是空间目标最常见的微运动之一。由于目标的进动由旋转运动和圆锥运动的合成组成，因此其雷达回波的调制特性比简单旋转目标的调制特性更为复杂。这使得很难从物体的雷达回波中提取出准确的微动特征和结构特征。在本文中，基于分布式雷达网络，我们提出了一种提取锥形空间目标的三维（3-D）进动特征的算法。该算法利用了分布式雷达网络的多视角优势。在本文中，我们首先分析了岁差引起的微多普勒（mD）对距离慢时平面的影响，然后分步提出了算法，其中详细讨论了一些相关问题，并分别进行了仿真。给出。借助于所提出的算法，可以精确地提取目标的一些3-D进动特征和结构特征，例如3-D圆锥矢量，旋转周期，进动周期，进动角和锥底半径。目标的长度也可以估算。在本文的最后一部分，我们还讨论了所提出算法的鲁棒性以及相应的仿真结果。

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