We are concerned with the inverse scattering problems associated with incomplete measurement data. It is a challenging topic of increasing importance in many practical applications. Based on a prototypical working model, we propose a machine learning based inverse scattering scheme, which integrates a CNN (convolution neural network) for the data retrieval. The proposed method can effectively cope with the reconstruction under limited-aperture and/or phaseless far-field data. Numerical experiments verify the promising features of our new scheme.

中文翻译：

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基于机器学习的数据检索用于不完整数据的逆散射问题

我们关注与不完整测量数据相关的逆散射问题。在许多实际应用中，这是一个越来越重要的具有挑战性的话题。基于原型工作模型，我们提出了一种基于机器学习的逆散射方案，该方案集成了用于数据检索的 CNN（卷积神经网络）。所提出的方法可以有效地应对有限孔径和/或无相远场数据下的重建。数值实验验证了我们新方案的有前途的特征。