Synthetic landmine scene development and validation in DIRSIG

Detection and neutralization of surface-laid and buried landmines has been a slow and dangerous endeavor for military forces and humanitarian organizations throughout the world. In an effort to make the process faster and safer, scientists have begun to exploit the ever-evolving passive electro-optical realm of detectors, both from a broadband perspective and a multi or hyperspectral perspective. Carried with this exploitation is the development of mine detection algorithms that take advantage of spectral features exhibited by mine targets, only available in a multi or hyperspectral data set. Difficulty in algorithm development arises from a lack of robust data, which is needed to appropriately test the validity of an algorithm\u27s results. This paper discusses the development of synthetic data using the Digital Imaging and Remote Sensing Image Generation (DIRSIG) model. A synthetic landmine scene has been modeled representing data collected at an arid US Army test site by the University of Hawaii\u27s Airborne Hyperspectral Imager (AHI). The synthetic data has been created and validated to represent the surrogate minefield thermally, spatially, spectrally, and temporally over the 7.9 to 11.5 micron region using 70 bands of data. Validation of the scene has been accomplished by direct comparison to the AHI truth data using qualitative band to band visual analysis, radiance curve comparison, Rank Order Correlation comparison, Principle Components dimensionality analysis, Gray Level Co-occurrence Matrix and Spectral Co-occurrence Matrix analysis, and an evaluation of the R(x) algorithm\u27s performance. This paper discusses landmine detection phenomenology, describes the steps taken to build the scene, modeling methods utilized to overcome input parameter limitations, and compares the synthetic scene to truth data

Preconcentration techniques for trace explosive sensing

This project has received funding from NATO Science for Peace & Security under grant agreement MYP G5355, the European Union’s Seventh Framework Programme for research, technological development and demonstration under agreement no 284747, and the EPSRC under EP/K503940/1.Trace sensing of explosive vapours is a method in humanitarian demining and Improvised Explosives Device (IED) detection that has received increasing attention recently, since accurate, fast, and reliable chemical detection is highly important for threat identification. However, trace molecule sampling in the field can be extremely difficult due to factors including weather, locale, and very low vapour pressure of the explosive. Preconcentration of target molecules onto a substrate can provide a method to collect higher amounts of analyte for analysis. We used the commercial fluoropolymer Aflas as a preconcentrator material to sorb explosive molecules to the surface, allowing subsequent detection of the explosives via the luminescence quenching response from the organic polymer Super Yellow. The preconcentration effect of Aflas was confirmed and characterised with 2,4-DNT, prior to field sampling being conducted at a test minefield in Croatia by placing preconcentration strips in the entrance of the hives, where honeybees have collected explosive materials during free-flying. In this work we show for the first time a method for confirmation of landmines combining honeybee colonies containing a preconcentration material and subsequent monitoring of luminescence quenching.PostprintPeer reviewe

Detection of Buried Non-Metallic (Plastic and FRP Composite) Pipes Using GPR and IRT

This research investigated alternative strategies for making buried non-metallic pipes (CFRP, GFRP, and PVC) easily locatable using Ground Penetrating Radar (GPR). Pipe diameters up to 12 and buried with up to 4 ft. of soil cover were investigated. The findings of this study will help address the detection problem of non-metallic pipelines and speed the adoption of composite pipes by the petroleum and natural gas industry. The research also investigated the possibility of locating buried pipes transporting hot fluids using Infrared Thermography (IRT). Results from the study have shown that, using carbon fabric and aluminum tape overlay on non‑metallic pipes (GFRP or PVC for this study) before burying significantly increases the reflected GPR signal amplitude, thereby making it easier to locate such pipelines using GPR. The reflected GPR signal amplitude for pipe sections with carbon fabric or aluminum foil overlays was found to have increased by a factor of up to 4.52 times, and 2.02 times on average across all the pipe sections tested, from the baseline (unwrapped) pipe sections. The research also highlights the importance of using the correct antenna frequency for detecting buried pipes in wet soil conditions. Wet soils with high electrical conductivity and dielectric constants have higher radar signal attenuations that significantly affect the penetration depth and returned signal amplitudes from buried objects. A 200 MHz frequency antenna was found in this study to be ideal for locating the buried pipes in all soil moisture conditions. The 200 MHz antenna was able to detect buried pipes up to the maximum 4 ft. depth of soil cover that was studied experimentally. Numerical estimation using the same soil from the experiment shows that this antenna can penetrate up to a depth of at least 5.5 ft. in very wet clay soils with volumetric water content of 0.473. After evaluating the attenuation characteristics of different radar antennae, it was found that material/ohmic attenuation is constant across a range of antenna frequencies; the increase in GPR signal attenuation associated with higher antenna frequencies was found to be a result of scattering attenuation from subsurface inhomogeneity/clutter. Scattering attenuation is however usually ignored in literature, resulting in erroneous estimation of radar signal attenuation. Finally, laboratory study proved that, heat from a buried pipeline transporting hot fluid can propagate through the soil to the surface and be detected using IRT. Additionally, a 6 diameter steam pipe with a 6 minimum insulation and buried with 2.5 – 3 ft. of soil cover was easily detected in varying soil moisture conditions during different seasons throughout the year using IRT in the field environment. The successful application of IRT in detecting this pipe proves the potential for using this technique in locating buried pipes transporting hot fluids such as steam or petroleum products from production wells or refinery plants