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首页> 外文期刊>Geoscience and Remote Sensing Letters, IEEE >MUSIC Algorithms for Grid Diagnostics
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MUSIC Algorithms for Grid Diagnostics

机译:用于网格诊断的MUSIC算法

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The problem of detecting and localizing missing scatterers (faults) inside a known grid of small cross-sectional perfect-electric-conducting cylinders is dealt with. The case of a TM scalar 2-D geometry is considered, and the Multiple Signal Classification (MUSIC) spectral estimation technique is employed. Two different scattering models are employed and compared. The first one aims at localizing present objects within a free-space background medium. The second one aims at detecting the faults and exploits the Green's function of the full grid. The limitations of the first approach are pointed out and connected to the maximum dimension of the data space. Then, the second approach performs successfully when the fault number is lower than scattering objects.
机译:解决了在已知的具有小横截面的理想导电圆柱体的网格内检测和定位丢失的散射体(故障)的问题。考虑TM标量2-D几何的情况,并采用多信号分类(MUSIC)频谱估计技术。使用和比较了两种不同的散射模型。第一个目标是在自由空间背景介质中定位当前对象。第二个目标是检测故障并利用整个网格的格林功能。指出了第一种方法的局限性,并将其连接到数据空间的最大维度。然后,当故障数小于散射对象时,第二种方法成功执行。

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