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Oscillating Targets in Airborne SAR Images

机译:机载SAR图像中的振荡目标

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Synthetic aperture radar (SAR) processors generally assume that the scene reflectors are stationary over the time of integration of the image. When this is not the case, various kinds of image distortions may occur, such as target displacement or smearing. In the present paper, oscillating targets are considered. It is shown that such targets are smeared in azimuth to an extent determined by the amplitude and frequency of the oscillation. The reason may be stated in terms of the slow-time Doppler shift of the target. The Doppler shift is not constant, but varies with aperture time. We show that time-frequency analysis provides useful tools to handle problems of this kind. The choice of analysis method is often difficult. Here, we compare several methods of the Cohen's class, and show good results with the data adaptive optimal kernel method. This method, being adaptive, dispenses with some of the trial-and-error often necessary with quadratic methods. We show data from a controlled experiment where oscillating reflectors were placed within a scene imaged by an airborne SAR, system. The reflectors are smeared in azimuth. We estimate the amplitude and frequency of the oscillations from the time-frequency distributions.
机译:合成孔径雷达(SAR)处理器通常假定场景反射器在图像积分期间是固定的。否则,可能会发生各种图像失真,例如目标位移或拖尾。在本文中,考虑了振荡目标。结果表明,这些目标在方位角上的涂抹程度取决于振荡的幅度和频率。可以根据目标的慢速多普勒频移来说明原因。多普勒频移不是恒定的,而是随光圈时间而变化的。我们表明时频分析提供了有用的工具来处理此类问题。分析方法的选择通常很困难。在这里,我们比较了Cohen类的几种方法,并用数据自适应最优核方法显示了良好的结果。这种方法是自适应的,省去了二次方法经常需要的反复试验。我们显示的是来自受控实验的数据,其中将振荡反射器放置在机载SAR系统成像的场景内。反射器以方位角涂抹。我们从时频分布估计振荡的幅度和频率。

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