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首页> 外文期刊>Geoscience and Remote Sensing, IEEE Transactions on >Temporal Orthogonal Projection Inversion for EMI Sensing of UXO
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Temporal Orthogonal Projection Inversion for EMI Sensing of UXO

机译:UXO的EMI时域正交投影反演

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摘要

We present a new approach for inverting time-domain electromagnetic data to recover the location and magnetic dipole polarizations of a limited number of buried objects. We form the multichannel electromagnetic induction (EMI) sensor data as a spatial–temporal response matrix (STRM). The rows of the STRM correspond to measurements sampled at different time channels from one sensor and the columns correspond to measurements sampled at the same time channel from different sensors. The singular value decomposition of the STRM produces the left and right singular vectors that are related to the sensor and the temporal spaces, respectively. If the effective rank of the STRM is $r$, then the first $r$ singular vectors span signal subspaces (SS), and the remaining singular vectors span the noise subspaces. The original data are projected onto the SS, and the temporal orthogonal projection inversion (TOPI) uses these data in a nonlinear inverse problem to solve for source locations of the objects. The polarizations of the targets are then obtained by solving a linear optimization problem in the original data domain. We present theoretical and numerical analyses to investigate the singular value system of the STRM and the sensitivity of the TOPI to the size of an SS. Only a few subspace vectors are required to generate locations of the objects. The results are insensitive to the exact choice of rank, and this differs from usual methods that involve selecting the number of time channels to be used in the inversion and carefully estimating associated uncertainties. The proposed approach is evaluated using the synthetic and real multistatic EMI data.
机译:我们提出了一种时域电磁数据反演的新方法,以恢复有限数量的掩埋物体的位置和磁偶极极化。我们将多通道电磁感应(EMI)传感器数据形成为时空响应矩阵(STRM)。 STRM的行对应于从一个传感器在不同时间通道采样的测量值,列对应于从不同的传感器在同一时间通道采样的测量值。 STRM的奇异值分解产生分别与传感器和时间空间有关的左奇异矢量和右奇异矢量。如果STRM的有效等级为 $ r $ ,则第一个 $ r $ 奇异矢量跨越信号子空间(SS),其余奇异矢量跨越噪声子空间。原始数据被投影到SS上,并且时间正交投影反演(TOPI)在非线性反问题中使用这些数据来求解对象的源位置。然后,通过解决原始数据域中的线性优化问题来获得目标的极化。我们目前进行理论和数值分析,以研究STRM的奇异值系统以及TOPI对SS大小的敏感性。只需几个子空间矢量即可生成对象的位置。结果对等级的确切选择不敏感,这与通常的方法不同,后者涉及选择反演中使用的时间通道数量并仔细估计相关的不确定性。利用合成的和实际的多静态EMI数据对所提出的方法进行了评估。

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