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The minimum sample region required to predict the far-field RCS from the bistatic near-field data

机译:从双基地近场数据预测远场RCS所需的最小样本区域

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For complex targets, a full bistatic near-field scattering data is required for measuring the far field radar cross section (RCS) in principle, but the acquisition time and the computational effort may be prohibitive. In this paper, we consider the far-field monostatic RCS is presented by exploiting only the near-field data relative to an angular region centered on the direction of interest, this area is the minimum sample region. Since the corner reflector is a typical multiple scattering structure, the size of the surface scanned from the near-field depends on scattering characteristics of the target. Analyses were conducted on the near-field data, we can found a zone which contains mutation of scattering characteristic. When collecting the bistatic near-field scattering data, most of the scattering information of the target can be obtained as long as the mutation zone is covered. Therefore, a fast and efficient algorithm is obtained through the analysis and simulation.
机译:对于复杂目标,原则上需要完整的双基地近场散射数据来测量远场雷达横截面(RCS),但采集时间和计算工作可能会令人望而却步。在本文中,我们认为通过仅利用相对于以关注方向为中心的角度区域的近场数据来呈现远场单站RCS,该区域是最小样本区域。由于角反射器是典型的多重散射结构,因此从近场扫描的表面尺寸取决于目标的散射特性。对近场数据进行了分析,我们发现一个包含散射特征突变的区域。当收集双基地近场散射数据时,只要覆盖突变区域,就可以获得目标的大部分散射信息。因此,通过分析和仿真获得了一种快速有效的算法。

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