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Comparison of various enhanced radar imaging techniques

机译:各种增强型雷达成像技术的比较

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Abstract: Recently, many techniques have been proposed to enhance the quality of radar images obtained using SAR and/or ISAR. These techniques include spatially variant apodization (SVA), adaptive sidelobe reduction (ASR), the Capon method, amplitude and phase estimation of sinusoids (APES) and data extrapolation. SVA is a special case of ASR; whereas the APES algorithm is similar to the Capon method except that it provides a better amplitude estimate. In this paper, the ASR technique, the APES algorithm and data extrapolation are used to generate radar images of two experimental targets and an airborne target. It is shown that although for ideal situations (point targets) the APES algorithm provides the best radar images (reduced sidelobe level and sharp main lobe), its performance degrades quickly for real world targets. The ASR algorithm gives radar images with low sidelobes but at the cost of some loss of information about the target. Also, there is not much improvement in radar image resolution. Data extrapolation, on the other hand, improves image resolution. In this case one can reduce the sidelobes by using non-uniform weights. Any loss in the radar image resolution due to non-uniform weights can be compensated by further extrapolating the scattered field data.!14
机译:摘要:最近,已经提出了许多技术来提高使用SAR和/或ISAR获得的雷达图像的质量。这些技术包括空间变异变迹(SVA),自适应旁瓣减小(ASR),Capon方法,正弦波的幅度和相位估计(APES)以及数据外推。 SVA是ASR的特例;而APES算法与Capon方法相似,但它提供了更好的幅度估计。在本文中,ASR技术,APES算法和数据外推用于生成两个实验目标和一个机载目标的雷达图像。结果表明,尽管在理想情况下(点目标),APES算法可提供最佳的雷达图像(降低的旁瓣水平和锋利的主瓣),但对于真实世界的目标,其性能会迅速下降。 ASR算法可提供低旁瓣的雷达图像,但会损失一些有关目标的信息。同样,雷达图像分辨率也没有太大的提高。另一方面,数据外推可提高图像分辨率。在这种情况下,可以通过使用不均匀的权重来减少旁瓣。可以通过进一步外推散射场数据来补偿由于权重不均匀而导致的雷达图像分辨率的任何损失。14

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