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Improving compressive sensing results in radar using multiple reconstructions

机译:使用多重重构改善雷达的压感结果

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Compressive sensing based reconstruction introduces noise which is dependent on a number of factors, in particular the choice of representation basis. In this paper we show how multiple reconstructions using different bases can be used to more accurately retrieve target information in a radar signal. We focus on signal averaging as a technique for achieving these improvements, and discuss the effectiveness of this strategy as well as a few potential problems and limitations inherent in such a strategy. We also provide a basic example of a way of improving this averaging technique, and provide a template for further development and case-by-case fine tuning.
机译:基于压缩的基于压缩的重建引入了取决于许多因素的噪声,特别是基于表示的选择。在本文中,我们示出了如何使用不同碱基的多个重建如何在雷达信号中更准确地检索目标信息。我们专注于信号平均作为实现这些改进的技术,并讨论这种策略的有效性以及这种策略中固有的一些潜在问题和局限性。我们还提供了一种改进该平均技术的方法的基本示例,并为进一步开发和逐个微调调整提供模板。

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