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Fixed-point iterations in determining a Tikhonov regularization parameter in Kirsch's factorization method

机译:Kirsch因式分解方法中确定Tikhonov正则化参数的定点迭代

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摘要

Kirsch's factorization method is a fast inversion technique for visualizing the profile of a scatterer from measurements of the far-field pattern. The mathematical basis of this method is given by the far-field equation, which is a Fredholm integral equation of the first kind in which the data function is a known analytic function and the integral kernel is the measured (and therefore noisy) far-field pattern. We present a Tikhonov parameter choice approach based on a fast fixed-point iteration method which constructs a regularization parameter associated with the corner of the L-curve in log-log scale. The performance of the method is evaluated by comparing our reconstructions with those obtained via the L-curve and we conclude that our method yields reliable reconstructions at a lower computational cost.
机译:Kirsch的因子分解方法是一种快速的反演技术,可通过对远场模式的测量来可视化散射体的轮廓。该方法的数学基础由远场方程给出,该方程是第一类Fredholm积分方程,其中数据函数是已知的解析函数,而积分核是测得的(因此有噪声)远场模式。我们提出一种基于快速定点迭代方法的Tikhonov参数选择方法,该方法构造与对数对数刻度中与L曲线拐角相关的正则化参数。通过将我们的重构与通过L曲线获得的重构进行比较,可以评估该方法的性能,并得出结论,我们的方法以较低的计算成本产生了可靠的重构。

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