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Multi-chromatic analysis of SAR images for target analysis

机译:SAR图像的多色分析,用于目标分析

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Multi-Chromatic Analysis (MCA) of SAR images relays on exploring sub-band images obtained by processing portions of range spectrum located at different frequency positions. It has been applied to interferometric pairs for phase uwrapping and height computation. This work investigates two promising applications: the comparison between the frequency-persistent scatterers (PS_(fd)) and the temporal-persistent scatterers (PS), and the use of inter-band coherence of a single SAR image for vessel detection. The MCA technique introduces the concept of frequency-stable targets, i.e. objects exhibiting stable radar returns across the frequency domain which is complementary to that of temporal stability at the base of PS interferometry. Both spotlight and stripmap TerraSAR-X images acquired on the Venice Lagoon have been processed to identify PS_(fd) and PS. Different populations have been analyzed to evaluate the respective characteristics and the physical nature of PS_(fd) and PS. Concerning the spectral coherence, it is derived by computing the coherence between sub-images of a single SAR acquisition. In the presence of a random distribution of surface scatterers, spectral coherence must be proportional to sub-band intersection of sub-images. This model is fully verified when observing measured spectral coherence on open see areas. If scatterers distribution departs from this distribution, as for manmade structures, spectral coherence is preserved. We investigated the spectral coherence to perform vessel detection on sea background by using spotlight images acquired on Venice Lagoon. Sea background tends to lead to very low spectral coherence while this latter is preserved on the targeted vessels, even for very small ones. A first analysis shows that all vessels observable in intensity images are easily detected in the spectral coherence images which can be used as a complementary information channel to constrain vessel detection.
机译:SAR图像的多色分析(MCA)依靠探索通过处理位于不同频率位置的部分范围频谱获得的子带图像。它已被应用于干涉对,用于相位包裹和高度计算。这项工作调查了两个有希望的应用:频率持久性散射体(PS_(fd))和时间持久性散射体(PS)之间的比较,以及单个SAR图像的带间相干性在血管检测中的使用。 MCA技术引入了频率稳定目标的概念,即,在整个频域上表现出稳定雷达回波的对象,这与基于PS干涉测量法的时间稳定性相辅相成。在威尼斯泻湖上采集的聚光灯和带状地图TerraSAR-X图像均已进行处理,以识别PS_(fd)和PS。分析了不同的种群,以评估PS_(fd)和PS的各自特征和物理性质。关于频谱相干性,它是通过计算单个SAR采集的子图像之间的相干性得出的。在存在表面散射体的随机分布的情况下,光谱相干性必须与子图像的子带相交成比例。当在开阔的视野观察观测到的光谱相干性时,该模型得到了充分验证。如果散射体分布偏离此分布,则对于人造结构,将保留光谱相干性。我们调查了光谱相干性,以通过使用在威尼斯泻湖上采集的聚光图像在海面背景上进行船舶检测。海洋背景往往导致非常低的光谱相干性,而后者却保留在目标船只上,即使是很小的船只也是如此。首次分析表明,在光谱相干图像中可以轻松检测到强度图像中可观察到的所有血管,这些血管可以用作补充信息通道来约束血管检测。

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