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Multiplicative-Regularized FFT Twofold Subspace-Based Optimization Method for Inverse Scattering Problems

机译:基于乘法正则化FFT二次子空间的逆散射优化方法

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摘要

In this paper, we combine two techniques together, i.e., the fast Fourier transform-twofold subspace-based optimization method (FFT-TSOM) and multiplicative regularization (MR) to solve inverse scattering problems. When applying MR to the objective function in the FFT-TSOM, the new method is referred to as MR-FFT-TSOM. In MR-FFT-TSOM, a new stable and effective strategy of regularization has been proposed. MR-FFT-TSOM inherits not only the advantages of the FFT-TSOM, i.e., lower computational complexity than the TSOM, better stability of the inversion procedure, and better robustness against noise compared with the SOM, but also the edge-preserving ability from the MR. In addition, a more relaxed condition of choosing the number of current bases being used in the optimization can be obtained compared with the FFT-TSOM. Particularly, MR-FFT-TSOM has even better robustness against noise compared with the FFT-TSOM and multiplicative regularized contrast source inversion (MR-CSI). Numerical simulations including both inversion of synthetic data and experimental data from the Fresnel data set validate the efficacy of the proposed algorithm.
机译:在本文中,我们将两种技术结合在一起,即基于快速傅立叶变换-双重子空间的优化方法(FFT-TSOM)和乘法正则化(MR)来解决逆散射问题。将MR应用于FFT-TSOM中的目标函数时,新方法称为MR-FFT-TSOM。在MR-FFT-TSOM中,提出了一种新的稳定有效的正则化策略。与SOM相比,MR-FFT-TSOM不仅继承了FFT-TSOM的优点,即比TSOM具有更低的计算复杂度,反演过程的稳定性更高,抗噪声的鲁棒性,而且还继承了FFT-TSOM的边缘保留能力。先生。此外,与FFT-TSOM相比,可以获得更宽松的条件,可以选择最优化中使用的当前碱基数。特别是,与FFT-TSOM和乘法正则对比源反演(MR-CSI)相比,MR-FFT-TSOM具有更好的抗噪声鲁棒性。包括合成数据和菲涅耳数据集的实验数据的数值模拟都验证了该算法的有效性。

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