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Improved background and clutter reduction for pipe detection under pavement using Ground Penetrating Radar (GPR)

2019; Elsevier BV; Volume: 172; Linguagem: Inglês

10.1016/j.jappgeo.2019.103918

1879-1859

Hao Bai, Joseph V. Sinfield,

Indoor and Outdoor Localization Technologies

Pavement drainage systems are one of the key drivers of pavement function and longevity, and effective drain maintenance can significantly extend a pavement's service life. Maintenance of these drains, however, is often hampered by the challenge of locating the drains. Ground Penetrating Radar (GPR) typically offers a rapid and effective method to detect these underground targets. However, typical detection schema that rely upon the observation of the hyperbolic return from a GPR scan of a buried conduit still tend to miss many of the older drains beneath pavements as they may be partially or fully filled with sediment and/or may be fabricated from clay or other earthen materials, yielding a return signal that is convolved with significant background noise. To manage this challenge, this paper puts forward an improved background noise and clutter reduction method to enhance the target signals in what amounts to a constructed environment that tends to have more consistent subsurface properties than one might encounter in a general setting. Within this technique, two major algorithms are employed. Algorithm 1 is the core of this method, and plays the role of reducing background noise and clutter. Algorithm 2 is supplementary, and helps eliminate anomalous discontinuous returns generated by the equipment itself, which could otherwise lead to false detection indications in the output of Algorithm 1. Instead of traditional 2-D GPR images, the result of the proposed algorithms is a 1-D plot along the survey line, highlighting a set of "points of interest" that could indicate buried drain locations identified at any given GPR operating frequency. Subsurface exploration using two different operating frequencies, 900 MHz and 400 MHz herein, is then employed to further enhance detection confidence. Points of interest are ultimately coded to define the confidence of the detection. Code -1 represents a false alarm; code 0 represents a possible drain location that needs further examination; codes 1, 2 and 3 represent successful detection with different levels of confidence. Comparing the final result of proposed algorithms with the original GPR images, the improved algorithm is demonstrated to provide significantly improved detection results, and could potentially be applied to similar problems in other contexts.