Automatic Detection of a Subsurface Wire Using an Electromagnetic Gradiometer
Automatic Detection of a Subsurface Wire Using an Electromagnetic Gradiometer
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DOI：
10.1109/tgrs.2012.2201162
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发表时间：
2013-01-01
影响因子：
8.2
通讯作者：
McKenna, Jason R.
中科院分区：
文献类型：
--
作者：
McKenna, Sean P.;Parkman, Kevin B.;McKenna, Jason R.
提出了一种基于模型的相关检测方案，其目的是以自动化的方式检测和定位地下隧道基础设施。我们的目标是开发一种全面的检测技术，可以被非专家部署和成功使用，同时足够强大，有效。我们的相关检测算法依赖于一个图书馆的模型信号，使用一个分析模型的一个薄的地下线在均匀的半空间。使用有源发射器源（12、20或200 kHz）照亮电线，并使用便携式电磁梯度计（EMG）系统感测其响应。使用合成数据和接收器工作特性（ROC）分析，以及在现场测试中收集的实验数据的检测器的性能进行评估。初步的ROC结果表明，在足够的信噪比，检测器可以实现检测概率大于0.9，相应的误报率小于每1000米。现场测试的结果表明，来自EMG的响应可用于检测和定位（水平方向0.5 m内）至少7 m深度的金属丝目标。我们相信EMG系统和相关检测器联合收割机可以形成一种很有前途的技术，用于检测隧道基础设施，可以由专家使用，更重要的是，非专家也可以使用。
A model-based correlation detection scheme is presented with the aim of detecting and localizing subsurface tunnel infrastructure in an automated fashion. Our goal is to develop a comprehensive detection technology that can be fielded and successfully used by nonexperts, while simultaneously being sufficiently robust as to be effective. Our correlation detection algorithm relies on a library of model signals that are generated using an analytical model of a thin subsurface wire in a homogeneous half-space. The wire is illuminated using an active transmitter source (12, 20, or 200 kHz), and its response is sensed using a man-portable electromagnetic gradiometer (EMG) system. The performance of the detector is assessed using synthetic data and receiver operating characteristic (ROC) analysis as well as experimental data collected during a field test. Preliminary ROC results indicate that at sufficient signal-to-noise ratio, the detector can achieve detection probabilities greater than 0.9 with corresponding false alarm rates of less than one every 1000 m. Results from the field tests revealed that the responses from the EMG can be used to detect and localize (to within 0.5 m in the horizontal) a wire target down to a depth of at least 7 m. We believe the EMG system and correlation detector combine to form a promising technology for detecting tunnel infrastructure that can be used by experts and, more importantly, nonexperts as well.