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Wavelet-based algorithms for scattering and inverse scattering problems.

机译:基于小波的散射和逆散射问题算法。

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摘要

The dissertation consists of two parts: scattering and inverse scattering. In the first part, the Coifman wavelet-based moment method with ratio-progressive approximation (RPA) scheme is developed to evaluate the singular integrals encountered in the magnetic field integral equation. As a result, the computation counts of the moment matrix are reduced from O(N 2) to O(N), owing to the one-point quadrature of the Coiflet. The new algorithm is applied to both the PEC and dielectric rough surfaces. New numerical results show that the backscattering enhancement on s0hh from the finite conductivity of the surface is unprecedentedly close to that of PEC surfaces with half the physical roughness, while the angular pattern of the cross-polarization part is more dependent on the surface curvature. The simulations using published soil parameters show that the Coiflet-based fast algorithm is sensitive and accurate in predicting small scattering coefficients from dielectric surfaces. Scattering from dielectric surfaces is more complicated than in the PEC case, e.g., backscattering enhancement and complex surface waves, which are observed in these simulations.; In the second part, an efficient deconvolution of the measurement system response is developed for time-domain near-field ISAR imaging. Due to its impulse-like waveform, the backscattering waveform from an electrically large conducting sphere is adopted as the system response to restore the impulse response of the scattered field, and to reconstruct the ISAR imaging. This deconvolution is discretized into a matrix equation, and the least-squares solution to the matrix equation is found by the conjugate gradient method. The resulting images are c with most smearing removed. Furthermore, the Coifman wavelet of the 6th order is employed to replace the system function of the 1st and 3rd derivatives of Gaussian functions. Due to the orthogonality and compact support of the Coiflets, the deconvolution process is accelerated by a factor of 22 without sacrificing the image quality.
机译:本文分为两个部分:散射和逆散射。在第一部分中,开发了基于Coifman小波的矩量法和比例渐进近似(RPA)方案,以评估磁场积分方程中遇到的奇异积分。结果,由于Coiflet的单点正交,矩矩阵的计算次数从O(N 2)减少到O(N)。新算法同时应用于PEC和电介质粗糙表面。新的数值结果表明,从表面的有限电导率到s0hh的反向散射增强前所未有地接近具有物理粗糙度一半的PEC表面的反向散射增强,而交叉极化部分的角度图案更多地取决于表面曲率。使用公开的土壤参数进行的模拟表明,基于Coiflet的快速算法在预测介电表面的小散射系数时灵敏且准确。从电介质表面的散射比在PEC情况下更复杂,例如,在这些模拟中观察到的反向散射增强和复杂的表面波。在第二部分中,针对时域近场ISAR成像,开发了一种有效的对测量系统响应进行去卷积的方法。由于其脉冲状波形,因此将来自大导电球体的反向散射波形用作系统响应,以恢复散射场的脉冲响应并重建ISAR成像。该解卷积被离散化为一个矩阵方程,并通过共轭梯度法找到该矩阵方程的最小二乘解。所产生的图像被去除了大部分污点的c。此外,采用6阶的Coifman小波来代替高斯函数的一阶和三阶导数的系统函数。由于Coiflet的正交性和紧凑的支持性,在不牺牲图像质量的情况下,反卷积过程的速度提高了22倍。

著录项

  • 作者

    Lin, Jui-Yi.;

  • 作者单位

    Arizona State University.;

  • 授予单位 Arizona State University.;
  • 学科 Engineering Electronics and Electrical.
  • 学位 Ph.D.
  • 年度 2005
  • 页码 157 p.
  • 总页数 157
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 无线电电子学、电信技术;
  • 关键词

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