用于地下目标分类的稀疏二维磁反演方法

Yaxin Mu;Luzhao Chen;Xin Liu
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引用次数: 0

摘要

磁反演在目标分类和识别中发挥着重要作用。然而,传统的磁感应强度反演方法往往会陷入局部极小值,并且需要较高的存储空间和计算能力。本文提出了一种针对紧凑铁质目标的新型二维磁反演方法,将三维物体投影到二维反演平面上,并根据二维水平切片上的磁矩模量创建线性反演模型。紧凑异常目标在空间域由多个非零均匀连接网格组成,因此目标在梯度域是稀疏的,因为反演平面上的非零元素仅位于目标的边界。利用稀疏性,采用全变异压缩传感(TV-CS)框架解决二维磁反演问题,实现了隐藏目标的快速分类和识别。此外,还进行了数值模拟,实验结果表明,所提出的算法能够准确划分不同形状的目标,并区分实心和空心目标。对于一个紧凑的三维目标,空间分辨率为 0.5 米的二维磁反演时间为 0.096 秒,空间分辨率为 0.1 米的二维磁反演时间为 2.36 秒。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Sparse 2-D Magnetic Inversion Method for Subsurface Target Classification
Magnetic inversion plays an important role in target classification and recognition. However, traditional magnetic susceptibility inversion methods often fall into local minima, and require high storage space and computing power. This letter proposes a novel 2-D magnetic inversion method for compact ferrous targets, the 3-D object is projected onto a 2-D inversion plane and a linear inversion model based on the modulus of magnetic moment on a 2-D horizontal slice is created. The compact anomaly target is composed of multiple nonzero uniformly connected grids in spatial domain, so the target is sparse in the gradient domain, because the nonzero elements on the inversion plane are only located at the boundary of the target. Using the sparseness, total variation compressed sensing (TV-CS) framework is employed to solve the 2-D magnetic inversion problem, achieving rapid classification and identification of hidden targets. In addition, numerical simulations have been performed, and experimental results indicate that the proposed algorithm is able to accurately delineate targets of different shapes and distinguish between solid and hollow targets. For a compact 3-D target, the 2-D magnetic inversion time is 0.096 s with a spatial resolution of 0.5 m, and 2.36 s with a spatial resolution of 0.1 m.
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