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Merging Radar Data with Geographic Data for Visual Land Clutter Source Recognition

机译:合并雷达数据与地理数据以进行可视陆杂波源识别

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In the recent years, radar land clutter modelling and processing have been aided with Geographic Information Systems (GIS) and geodata in a few recognised researches such as in the Lincoln Laboratory. In our clutter research, one aspect is to study the possibilities of using GIS in clutter classification in Finnish environment. Since the automation of this process causes inaccurate results and a need to identify and label various types of land clutter sources through geographic data (geodata) exists, we propose an approach based on the visual interpretation of clutter. We have created a graphical visualisation tool for merging geodata with radar data interactively, including an option to select the shown type(s) of geodata. The source identification is based on the visual observation of the output. The tool can also be utilised when verifying simulated data.rnIn an example case, we have used the following geodata items: a base map, a terrain model, a database of tall structures, and a digital elevation model, but other types of geodata can be used as well. Although the potential to enhance the model is higher when more types of geodata are utilised, even with few carefully selected geodata items, clutter sources can be recognised adequately. This paper presents an illustrative demonstration using an air surveillance radar recording. This visual approach with the data merging tool has been useful, and the results have verified the practicability. The contribution of this paper focuses on supporting clutter classification research and improving the understanding of land clutter.
机译:近年来,在诸如林肯实验室等一些公认的研究中,借助地理信息系统(GIS)和地理数据辅助了雷达陆地杂波建模和处理。在我们的杂物研究中,一方面是研究在芬兰环境中将GIS用于杂物分类的可能性。由于此过程的自动化导致结果不准确,并且需要通过地理数据(地理数据)识别和标记各种类型的土地杂波源,因此,我们提出了一种基于视觉对杂波的解释的方法。我们创建了一个图形化的可视化工具,用于交互式地将地理数据与雷达数据合并,包括选择显示的地理数据类型的选项。源识别基于对输出的视觉观察。在验证模拟数据时,也可以使用该工具。在一个示例案例中,我们使用了以下地理数据项:底图,地形模型,高层结构数据库和数字高程模型,但是其他类型的地理数据也可以也可以使用。尽管当使用更多类型的地理数据时,增强模型的潜力更大,即使很少选择经过精心选择的地理数据,也可以充分识别杂波源。本文提出了使用空中监视雷达记录的说明性演示。这种带有数据合并工具的可视化方法非常有用,并且结果证明了其实用性。本文的贡献集中在支持杂波分类研究和增进对土地杂波的理解上。

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