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Block-Division Based Ultra-Wideband Fusion of Multiple Radar Bands for Resolution Enhanced Imagery

机译:基于块分割的多雷达带的超宽带融合,用于分辨率增强图像

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摘要

Parametric model based ultra-wideband fusion of multiple radar band data is usually not directly applicable to radar image processing for large sized complex targets, due to the fact that the required model orders are extremely high. In this paper, a block-division based data fusion technique is proposed, which can be used for multiple radar band fusion over ultra-wide bandwidth and image resolution enhancement for complex targets. In image domain, a large sized complex target is first divided into small blocks for each radar band. Each block is then equivalent to a small sized simple target whose missing phase history data between two different radar bands can be interpolated based on parametric models derived from the measurement data of the corresponding bands. Resolution enhanced image can then be reconstructed by integrating all the image blocks generated from the multi-band fused data. Numerical examples are presented to demonstrate the usefulness of the proposed technique.
机译:基于参数模型的多雷达频带数据的超宽带融合通常不适用于大型复杂目标的雷达图像处理,因为所需的模型订单非常高。在本文中,提出了一种基于块分割的数据融合技术,其可用于对复杂目标的超宽带宽和图像分辨率增强的多个雷达带融合。在图像域中,首先将大型复杂目标分成每个雷达带的小块。然后,每个块等同于小尺寸的简单目标,其两个不同的雷达频带之间的丢失阶段历史数据可以基于从相应频带的测量数据导出的参数模型来插入。然后可以通过集成从多频带融合数据生成的所有图像块来重建分辨率增强图像。提出了数值例证以证明所提出的技术的有用性。

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