Journal Article10.1109/tgrs.2023.3307651
Cavity Detection Using GPR With Small Offsets
Caleb Leibowitz,Anthony J. Weiss +1 more
- Vol. 61, pp 1-9
TL;DR: ZOP measurements are inexpensive yet not accurate enough for cavity detection. Small offsets in depth between the receiver and the transmitter improve accuracy.
read more
Abstract: Cross-borehole ground-penetrating radar (GPR) is one of the most effective tools available to detect underground cavities. These cavities are often detected from zero-offset profiling (ZOP) measurements, where the transmitter and the receiver are always at the same depth; the other common alternative is to use multiple-offset gathers (MOGs), such that a measurement is recorded with the transmitter and the receiver at every pair of depths. While the latter strategy sometimes allows one to compute a tomographic inversion and, in general, gives strictly more information, it is often prohibitively expensive to carry out such a survey, and the utility of many of these measurements is limited. ZOP measurements, on the other hand, are comparatively cheap to carry out, yet, it may not be possible to use these measurements alone to detect cavities with the required degree of accuracy. In this article, the use of measurements with a small offset in depth between the receiver and the transmitter is investigated, and it is shown that the use of only these measurements is a very favorable point in the expense-utility tradeoff. Along the way, it is shown that the manner in which traveltime is measured must be appropriate for the noise regime in which the GPR operates.
read more
Chat with Paper
AI Agents for this Paper
Find similar papers on Google Scholar, PubMed and Arxiv
Write a critical review of this paper
Analyze citations of this paper to find unaddressed research gaps
References
On the Optimality of the Simple Bayesian Classifier under Zero-One Loss
TL;DR: The Bayesian classifier is shown to be optimal for learning conjunctions and disjunctions, even though they violate the independence assumption, and will often outperform more powerful classifiers for common training set sizes and numbers of attributes, even if its bias is a priori much less appropriate to the domain.
Dielectric properties of soils in the 0.3-1.3-GHz range
TL;DR: The model underpredicts the real part of the dielectric constant for high-moisture cases and underestimates the imaginary part for all soils and moisture conditions, and significant variations for the real and imaginary part among soils with the same clay fractions but with clays of different specific surface areas.
711
Modelling ground penetrating radar by GprMax
TL;DR: A software tool that can be used to model GPR responses from arbitrarily complex targets called GprMax is presented and has been successfully employed in situations, where a deeper understanding of the operation and detection mechanism of GPR was required.
710