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Accurate 3-dimensional image reconstruction algorithm extending RPM method to ISAR model

机译:将RPM方法扩展到ISAR模型的精确3维图像重建算法

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Microwave 3-dimensional reconstruction techniques exploiting multiple ISAR (Inverse Synthetic Aperture Radar) images have been well established, and are suitable for the recognition of artificial targets such as aircrafts or ships. However, the existing algorithms assume only an aggregation of multiple points, and most require the tracking of the multiple points over multiple ISAR images. In the case of a solid object with a continuous boundary, such as a wire or polyhedral structure, these algorithms severely suffer from the inaccuracy for 3-D imaging, owing to scattering centers shifting on the target surface in terms of the observation angle. To tackle the above difficulty, this paper extends RPM (Range Points Migration) method to the ISAR observation model, where a double mono-static model is introduced to suppress cross-range ambiguity. Numerical simulation demonstrates that the proposed algorithm has a distinct advantage in accurate 3-D imaging, even for not point-wise targets.
机译:已经充分建立了利用多个ISAR(逆合成孔径雷达)图像的微波三维重建技术,并且适用于识别飞机或轮船等人造目标。但是,现有算法仅假设多个点的集合,并且大多数算法需要在多个ISAR图像上跟踪多个点。在具有连续边界的固体对象(例如线或多面体结构)的情况下,由于散射中心在观察角度上在目标表面上移动,因此这些算法严重遭受3-D成像的不准确性。为了解决上述困难,本文将RPM(测距点迁移)方法扩展到了ISAR观测模型,在该模型中引入了双单静态模型来抑制跨范围歧义。数值模拟表明,即使对于非逐点目标,该算法在精确的3D成像中也具有明显的优势。

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