论文标题
在多散射环境中，单声道静态数据的订单建模反演减少
Reduced order modeling inversion of mono static data in a multi-scattering environment
论文作者
论文摘要
数据驱动的还原订单模型（ROM）最近已成为解决逆散射问题以及对地震和声纳成像的应用的有效工具。这种方法的一种规范是，它需要完整的正方形多重输出/多输入（MIMO）矩阵值传输函数作为多维问题的数据。但是，合成孔径雷达（SAR）仅限于与矩阵传递函数对角线相对应的单个输入/单输出（SISO）测量值。在这里，我们提出了一种基于ROM的Lippmann-Schwinger方法，以克服这一缺点。构建了ROM以匹配每个源接收器对的数据，并且仅使用数据驱动的Gramian来构建相应源的内部解决方案。在2D和2.5D（3D传播和2D反射器）数值示例上证明了所提出的方法的效率。新的算法不仅抑制了出生的成像中看到的多个回声，而且还利用了它们从反射器的某些背面照明，从而提高了它们的映射质量。
The data-driven reduced order models (ROMs) have recently emerged as an efficient tool for the solution of the inverse scattering problems with applications to seismic and sonar imaging. One specification of this approach is that it requires the full square multiple-output/multiple-input (MIMO) matrix valued transfer function as data for multidimensional problems. The synthetic aperture radar (SAR), however, is limited to single input/single output (SISO) measurements corresponding to the diagonal of the matrix transfer function. Here we present a ROM based Lippmann-Schwinger approach overcoming this drawback. The ROMs are constructed to match the data for each source-receiver pair separately, and these are used to construct internal solutions for the corresponding source using only the data-driven Gramian. Efficiency of the proposed approach is demonstrated on 2D and 2.5D (3D propagation and 2D reflectors) numerical examples. The new algorithm not only suppresses multiple echoes seen in the Born imaging, but also takes advantage of illumination by them of some back sides of the reflectors, improving the quality of their mapping.
