GSA Connects 2022 meeting in Denver, Colorado

Paper No. 19-5
Presentation Time: 9:00 AM-1:00 PM

LASER DOPPLER VIBROMETER-BASED ACOUSTIC LANDMINE DETECTION USING A GEOSTATISTICAL SIGNATURE UNDER A PARTICULAR HYDRAULIC CONDITION


MAHMUD, Md Ilias1, HOLT, Robert M.1 and HICKEY, Craig J.2, (1)Department of Geology and Geological Engineering, University of Mississippi, Oxford, Oxford, MS 38677, (2)National Center for Physical Acoustics, University of Mississippi, Oxford, Oxford, MS 38677

Although laser doppler vibrometer (LDV) has shown promise for remotely and safely detecting buried landmines, the effects of the variabilities in soil physical properties like moisture content (MC) and matric potential (MP) are not thoroughly studied. Here, we examined the impacts of MC and MP on the surface vibrational velocity of the soil and used a semivariogram model to detect the presence of a buried landmine in a field site using a scanning single-beam LDV. The LDV-based measurements were carried out in natural state (background) and buried mine conditions under different excitation situations. The magnitude of the velocity was used as a regionalized variable to compute and model semivariogram to reflect a landmine signature. In-situ and laboratory measurements give the MC of soils at specific locations of the measurement plot. These MC values were used to estimate the MP of soil samples from their corresponding soil-water-characteristics curve. The variations in MC and MP of soils over the measurement plot were then compared with the changes in surface velocity. The result demonstrates that, in the presence of MC (μ= 8.65%) and MP (μ= 85.60 hPa), the mean surface velocity with a buried landmine is higher than that of the background, and it decreases with mine depth. However, the identification of a resonance frequency becomes complex, and the landmine signature is inconsistent over a broad frequency band. The landmine response can be repeatedly detected within a very narrow frequency band or at a specific frequency. At these frequencies, the semivariogram model with a buried landmine shows a stronger spatial autocorrelation than that of without a mine. The range of the semivariogram model indicates the landmine size. But, the variability in soil physical properties (like MC and MP) generates clutter that mask the unique semivariogram signature of a buried landmine. We conclude that the broadband nature of landmine response and the resonating frequency are affected by the presence of MC and MP making landmine detection even more complex. The semivariogram model detects landmine response when the spatial variability in soil physical properties is minimal. Detailed researches on a broader range of MC/MP would give a clearer picture of their control on surface velocity changes and their implications in landmine detection.