揭示基尔霍夫迁移的新见解,从菲涅尔实验数据集中快速有效地检测物体

IF 2.9 2区 数学 Q1 MATHEMATICS, APPLIED Computers & Mathematics with Applications Pub Date : 2024-10-17 DOI:10.1016/j.camwa.2024.10.019
Won-Kwang Park
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引用次数: 0

摘要

在本文中,我们考虑了从二维菲涅尔实验数据集中快速识别小型介质物体的有限孔径反向散射问题。为此,我们应用了基尔霍夫迁移(KM)成像技术,并根据生成的多静态响应矩阵设计了一个成像函数。利用基于积分方程的散射场表示公式,我们将成像函数表述为一阶整数贝塞尔函数的均匀收敛无穷级数,从理论上研究了 KM 的适用性。我们还利用菲涅尔实验数据集给出了数值模拟结果,以支持理论结果。
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Unveiling novel insights into Kirchhoff migration for a fast and effective object detection from experimental Fresnel dataset
In this paper, we consider a limited-aperture inverse scattering problem for a fast identification of small dielectric objects from two-dimensional Fresnel experimental dataset. To this end, we apply the Kirchhoff migration (KM) imaging technique and design an imaging function from the generated multi-static response matrix. Using the integral equation-based representation formula for the scattered field, we theoretically investigate the applicability of the KM by formulating the imaging function as a uniformly convergent infinite series of integer-order Bessel functions of the first kind. Numerical simulation results using the experimental Fresnel dataset are presented to support the theoretical result.
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来源期刊
Computers & Mathematics with Applications
Computers & Mathematics with Applications 工程技术-计算机:跨学科应用
CiteScore
5.10
自引率
10.30%
发文量
396
审稿时长
9.9 weeks
期刊介绍: Computers & Mathematics with Applications provides a medium of exchange for those engaged in fields contributing to building successful simulations for science and engineering using Partial Differential Equations (PDEs).
期刊最新文献
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