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3D Buried Utility Location Using A Marching-Cross-Section Algorithm for Multi-Sensor Data Fusion

Sensors (Basel, Switzerland), 2016-11, Vol.16 (11), p.1827 [Peer Reviewed Journal]

2016. This work is licensed under https://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;2016 by the authors; licensee MDPI, Basel, Switzerland. 2016 ;ISSN: 1424-8220 ;EISSN: 1424-8220 ;DOI: 10.3390/s16111827 ;PMID: 27827836

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  • Title:
    3D Buried Utility Location Using A Marching-Cross-Section Algorithm for Multi-Sensor Data Fusion
  • Author: Dou, Qingxu ; Wei, Lijun ; Magee, Derek R ; Atkins, Phil R ; Chapman, David N ; Curioni, Giulio ; Goddard, Kevin F ; Hayati, Farzad ; Jenks, Hugo ; Metje, Nicole ; Muggleton, Jennifer ; Pennock, Steve R ; Rustighi, Emiliano ; Swingler, Steven G ; Rogers, Christopher D F ; Cohn, Anthony G
  • Subjects: Algorithms ; buried utility location ; Cross sections ; Data integration ; Extended Kalman filter ; Gradiometers ; Ground penetrating radar ; LF electromagnetic fields ; Magnetic measurement ; marching-cross-section algorithm ; multi-sensor data fusion ; Multisensor fusion ; Pipes ; Segments ; Sensors ; Underground utilities ; Utility locating ; Vibroacoustics
  • Is Part Of: Sensors (Basel, Switzerland), 2016-11, Vol.16 (11), p.1827
  • Description: 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.
  • Publisher: Switzerland: MDPI AG
  • Language: English
  • Identifier: ISSN: 1424-8220
    EISSN: 1424-8220
    DOI: 10.3390/s16111827
    PMID: 27827836
  • Source: GFMER Free Medical Journals
    PubMed Central
    ROAD: Directory of Open Access Scholarly Resources
    ProQuest Central
    DOAJ Directory of Open Access Journals
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