3D Buried Utility Location Using A Marching-Cross-Section Algorithm for Multi-Sensor Data Fusion.
3D Buried Utility Location Using A Marching-Cross-Section Algorithm for Multi-Sensor Data Fusion.
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DOI：
10.3390/s16111827
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发表时间：
2016-11-02
期刊：
影响因子：
--
通讯作者：
Cohn AG
中科院分区：
文献类型：
--
作者：
Dou Q;Wei L;Magee DR;Atkins PR;Chapman DN;Curioni G;Goddard KF;Hayati F;Jenks H;Metje N;Muggleton J;Pennock SR;Rustighi E;Swingler SG;Rogers CD;Cohn AG
我们解决的问题，准确地定位埋公用事业段融合数据从多个传感器使用一种新的行军横截面（MCS）算法。在这项工作中使用了五种类型的传感器：探地雷达（GPR），被动磁场（PMF），磁力仪（MG），低频电磁场（LFEM）和振动声学（VA）。作为MCS算法的一部分，提出了一种新的扩展卡尔曼滤波器（EKF）的制定，用于将现有的实用程序跟踪从扫描横截面（SCS）行进到下一个;引入了新的规则，用于基于第一个SCS上的假设检测来初始化实用程序，并用于将预测的实用程序跟踪与以下SCS中的假设检测相关联。当不同传感器不共享公共扫描线时，或者当仅提供假设检测的坐标而没有实际测量扫描线的任何信息时，提出用于基于给定假设检测生成虚拟扫描线的算法。所提出的系统的性能进行评估与合成数据和真实的数据。实验结果表明，该算法可以同时定位多个埋地公用设施段，包括直线和曲线公用设施段，并能分离相交段。通过使用假设检测是管道或电缆的概率及其3D坐标，MCS算法能够区分彼此靠近的管道和电缆。MCS算法可用于后处理和现场处理。当它在现场使用时，当前scs上检测到的轨迹可以帮助确定下一条扫描线的位置和方向。所提出的“多公用设施多传感器”系统对埋地公用设施的数量或传感器的数量没有限制，并且使用的传感器数据越多，可以检测到的埋地公用设施段越多，位置和方向越准确。
We address the problem of accurately locating buried utility segments by fusing data from multiple sensors using a novel Marching-Cross-Section (MCS) algorithm. Five types of sensors are used in this work: Ground Penetrating Radar (GPR), Passive Magnetic Fields (PMF), Magnetic Gradiometer (MG), Low Frequency Electromagnetic Fields (LFEM) and Vibro-Acoustics (VA). As part of the MCS algorithm, a novel formulation of the extended Kalman Filter (EKF) is proposed for marching existing utility tracks from a scan cross-section (scs) to the next one; novel rules for initializing utilities based on hypothesized detections on the first scs and for associating predicted utility tracks with hypothesized detections in the following scss are introduced. Algorithms are proposed for generating virtual scan lines based on given hypothesized detections when different sensors do not share common scan lines, or when only the coordinates of the hypothesized detections are provided without any information of the actual survey scan lines. The performance of the proposed system is evaluated with both synthetic data and real data. The experimental results in this work demonstrate that the proposed MCS algorithm can locate multiple buried utility segments simultaneously, including both straight and curved utilities, and can separate intersecting segments. By using the probabilities of a hypothesized detection being a pipe or a cable together with its 3D coordinates, the MCS algorithm is able to discriminate a pipe and a cable close to each other. The MCS algorithm can be used for both post- and on-site processing. When it is used on site, the detected tracks on the current scs can help to determine the location and direction of the next scan line. The proposed “multi-utility multi-sensor” system has no limit to the number of buried utilities or the number of sensors, and the more sensor data used, the more buried utility segments can be detected with more accurate location and orientation.
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影响因子：
6.8
作者：
COX, H
通讯作者：
COX, H
影响因子：
2.5
作者：
RAUCH, HE;TUNG, F;STRIEBEL, CT
通讯作者：
STRIEBEL, CT
影响因子：
10.3
作者：
Li, Shuai;Cai, Hubo;Kamat, Vineet R.
通讯作者：
Kamat, Vineet R.
DOI：
10.1109/tgrs.2012.2201162
发表时间：
2013-01-01
影响因子：
8.2
作者：
McKenna, Sean P.;Parkman, Kevin B.;McKenna, Jason R.
通讯作者：
McKenna, Jason R.
影响因子：
6.9
作者：
Metje, N.;Atkins, P. R.;Thomas, A. M.
通讯作者：
Thomas, A. M.