Phenomenological Model for Infrared Emissions from High-Explosive Detonation Fireballs

Time-resolved infrared spectra were recently collected via a Fourier-transform spectrometer (FTS) from the detonation fireballs of two types of conventional military munitions (CMM) as well as uncased TNT and four types of enhanced novel explosives (ENEs). The CMM spectra are dominated by continuum emission, and a single-temperature Planckian distribution, modified for atmospheric attenuation, captures most of the variation in the data. Some evidence of selective emission is identified by systematic patterns in the fit residuals. The behavior of these systematic residuals affords a distinction between the two types of CMMs studied. The uncased TNT and ENE spectra appear strongly influenced by both continuum and selective emission. A physics-based spectral model is developed consisting of seven parameters: size, temperature, particulate absorption coefficient, and gas concentrations for H2O, CO2, CO, and HCl. Fitting affords a high-fidelity representation with features that correlate with HE characteristics. The hydrogen-to-carbon ratio (R) separates the TNT and ENE events and is consistent with stoichiometric expectations. Average values of R are compared with stoichiometry (in parenthesis): TNT 1.13 (0.79); ENE0B 9.2 (21.3); ENE1 4.9 (6.7); ENE2A 4.6 (5.8); ENE2B 6.5 (6.7). Bayesian discrimination boundary between TNT and ENE is R = 1.67 and the mean probability of error is less than 0.3% for this two-class problem. The Fisher ratio is 17.4 and ENE can be distinguished from TNT with 99% detection rate with corresponding false-alarm rate of less than 10-4%

Estimating Index of Refraction from Polarimetric Hyperspectral Imaging Measurements

Current material identification techniques rely on estimating reflectivity or emissivity which vary with viewing angle. As off-nadir remote sensing platforms become increasingly prevalent, techniques robust to changing viewing geometries are desired. A technique leveraging polarimetric hyperspectral imaging (P-HSI), to estimate complex index of refraction, N̂(ν̃), an inherent material property, is presented. The imaginary component of N̂(ν̃) is modeled using a small number of “knot” points and interpolation at in-between frequencies ν̃. The real component is derived via the Kramers-Kronig relationship. P-HSI measurements of blackbody radiation scattered off of a smooth quartz window show that N̂(ν̃) can be retrieved to within 0.08 RMS error between 875 cm−1 ≤ ν̃ ≤ 1250 cm−1. P-HSI emission measurements of a heated smooth Pyrex beaker also enable successful N̂(ν̃) estimates, which are also invariant to object temperature

Fast and Effective Techniques for LWIR Radiative Transfer Modeling: A Dimension-Reduction Approach

The increasing spatial and spectral resolution of hyperspectral imagers yields detailed spectroscopy measurements from both space-based and airborne platforms. These detailed measurements allow for material classification, with many recent advancements from the fields of machine learning and deep learning. In many scenarios, the hyperspectral image must first be corrected or compensated for atmospheric effects. Radiative Transfer (RT) computations can provide look up tables (LUTs) to support these corrections. This research investigates a dimension-reduction approach using machine learning methods to create an effective sensor-specific long-wave infrared (LWIR) RT model

Mid-IR Hyperspectral Imaging of Laminar Flames for 2-D Scalar Values

This work presents a new emission-based measurement which permits quantification of two-dimensional scalar distributions in laminar flames. A Michelson-based Fourier-transform spectrometer coupled to a mid-infrared camera (1.5 μm to 5.5 μm) obtained 256 × 128pixel hyperspectral flame images at high spectral (δν̃ = 0.75cm−1) and spatial (0.52 mm) resolutions. The measurements revealed line and band emission from H2O, CO2, and CO. Measurements were collected from a well-characterized partially-premixed ethylene (C2H4) flame produced on a Hencken burner at equivalence ratios, Φ, of 0.8, 0.9, 1.1, and 1.3. After describing the instrument and novel calibration methodology, analysis of the flames is presented. A single-layer, line-by-line radiative transfer model is used to retrieve path-averaged temperature, H2O, CO2 and CO column densities from emission spectra between 2.3 μm to 5.1 μm. The radiative transfer model uses line intensities from the latest HITEMP and CDSD-4000 spectroscopic databases. For the Φ = 1.1 flame, the spectrally estimated temperature for a single pixel 10 mm above burner center was T = (2318 ± 19)K, and agrees favorably with recently reported laser absorption measurements, T = (2348 ± 115)K, and a NASA CEA equilibrium calculation, T = 2389K. Near the base of the flame, absolute concentrations can be estimated, and H2O, CO2, and CO concentrations of (12.5 ± 1.7) %, (10.1 ± 1.0) %, and (3.8 ± 0.3) %, respectively, compared favorably with the corresponding CEA values of 12.8%, 9.9% and 4.1%. Spectrally-estimated temperatures and concentrations at the other equivalence ratios were in similar agreement with measurements and equilibrium calculations. 2-D temperature and species column density maps underscore the Φ-dependent chemical composition of the flames. The reported uncertainties are 95% confidence intervals and include both statistical fit errors and the propagation of systematic calibration errors using a Monte Carlo approach. Systematic errors could warrant a factor of two increase in reported uncertainties. This work helps to establish IFTS as a valuable combustion diagnostic tool

Learning Set Representations for LWIR In-Scene Atmospheric Compensation

Atmospheric compensation of long-wave infrared (LWIR) hyperspectral imagery is investigated in this article using set representations learned by a neural network. This approach relies on synthetic at-sensor radiance data derived from collected radiosondes and a diverse database of measured emissivity spectra sampled at a range of surface temperatures. The network loss function relies on LWIR radiative transfer equations to update model parameters. Atmospheric predictions are made on a set of diverse pixels extracted from the scene, without knowledge of blackbody pixels or pixel temperatures. The network architecture utilizes permutation-invariant layers to predict a set representation, similar to the work performed in point cloud classification. When applied to collected hyperspectral image data, this method shows comparable performance to Fast Line-of-Sight Atmospheric Analysis of Hypercubes-Infrared (FLAASH-IR), using an auto- mated pixel selection approach. Additionally, inference time is significantly reduced compared to FLAASH-IR with predictions made on average in 0.24 s on a 128 pixel by 5000 pixel data cube using a mobile graphics card. This computational speed-up on a low-power platform results in an autonomous atmospheric compensation method effective for real-time, onboard use, while only requiring a diversity of materials in the scene

Multimodal Representation Learning and Set Attention for LWIR In-Scene Atmospheric Compensation

A multimodal generative modeling approach combined with permutation-invariant set attention is investigated in this paper to support long-wave infrared (LWIR) in-scene atmospheric compensation. The generative model can produce realistic atmospheric state vectors (T;H2O;O3) and their corresponding transmittance, upwelling radiance, and downwelling radiance (TUD) vectors by sampling a low-dimensional space. Variational loss, LWIR radiative transfer loss and atmospheric state loss constrain the low-dimensional space, resulting in lower reconstruction error compared to standard mean-squared error approaches. A permutation-invariant network predicts the generative model low-dimensional components from in-scene data, allowing for simultaneous estimates of the atmospheric state and TUD vector. Forward modeling the predicted atmospheric state vector results in a second atmospheric compensation estimate. Results are reported for collected LWIR data and compared to Fast Line-of-Sight Atmospheric Analysis of Hypercubes - Infrared (FLAASH-IR), demonstrating commensurate performance when applied to a target detection scenario. Additionally, an approximate 8 times reduction in detection time is realized using this neural network-based algorithm compared to FLAASH-IR. Accelerating the target detection pipeline while providing multiple atmospheric estimates is necessary for many real-world, time sensitive tasks

Positron emission tomography detects evidence of viability in rest technetium-99m sestamibi defects

AbstractObjectives. The purpose of this study was to determine the relative value of single-photon emission computed tomographic (SPECT) imaging at rest using technetium-99m methoxyisobutyl isonitrile (technetium-99m sestamibi) with positron emission tomography for detection of viable myocardium.Background. Recent studies comparing positron emission tomography and thallium-201 reinjection with rest technetium-99m sestamibi imaging have suggested that the latter technique underestimates myocardial viability.Methods. Twenty patients with a previous myocardial infarction underwent rest technetium-99m sestamibi imaging and positron emission tomography using fluorine (F)-18 deoxyglucose and nitrogen (N)-13 ammonia. In each patient, circumferential profile analysis was used to determine technetium-99m sestamibi, F-18 deoxyglucose and N-13 ammonia activity (expressed as percent of peak activity) in nine cardiac segments and in the perfusion defect defined by the area having technetium-99m sestamibi activity <60%. Technetium-99m sestamibi defects were graded as moderate (50% to 59% of peak activity) and severe (<50% of peak activity). Estimates of perfusion defect size were compared between technetium-99m sestamibi and N-13 ammonia.Results. Sixteen (53%) of 30 segments with moderate defects and 16 (47%) of 34 segments with severe defects had ≥60% F-18 deoxyglocose activity considered indicative of viability. Fluorine-18 deoxyglucose evidence of viability was still present in 50% of segments with technetium-99m sestamibi activity <40%. There was no significant difference in the mean (± SD) technetium-99m sestamibi activity in segments with viable (40 ± 7%) and nonviable segments (49 ± 7%, p = 0.84). Of the 18 patients who had adequate F-18 deoxyglucose studies, the area of the technetium-99m sestamibi defect was viable in 5 (28%). In 16 patients (80%), perfusion defect size determined by technetium-99m sestamibi exceeded that measured by N-13 ammonia. The difference in defect size between technetium-99m sestamibi and N-13 ammonia was significantly greater in patients with viable (21 ± 9%) versus nonviable segments (7 ± 9%, p = 0.007).Conclusions. Moderate and severe rest technetium-99m sestamibi defects frequently have metabolic evidence of viability. Technetium-99m sestamibi SPECT yields larger perfusion defects than does N-13 ammonia positron emission tomography when the same threshold values are used

Accumulation of Tissue Factor Into Developing Thrombi In Vivo Is Dependent Upon Microparticle P-Selectin Glycoprotein Ligand 1 And Platelet P-Selectin

Using a laser-induced endothelial injury model, we examined thrombus formation in the microcirculation of wild-type and genetically altered mice by real-time in vivo microscopy to analyze this complex physiologic process in a system that includes the vessel wall, the presence of flowing blood, and the absence of anticoagulants. We observe P-selectin expression, tissue factor accumulation, and fibrin generation after platelet localization in the developing thrombus in arterioles of wild-type mice. However, mice lacking P-selectin glycoprotein ligand 1 (PSGL-1) or P-selectin, or wild-type mice infused with blocking P-selectin antibodies, developed platelet thrombi containing minimal tissue factor and fibrin. To explore the delivery of tissue factor into a developing thrombus, we identified monocyte-derived microparticles in human platelet–poor plasma that express tissue factor, PSGL-1, and CD14. Fluorescently labeled mouse microparticles infused into a recipient mouse localized within the developing thrombus, indicating that one pathway for the initiation of blood coagulation in vivo involves the accumulation of tissue factor– and PSGL-1–containing microparticles in the platelet thrombus expressing P-selectin. These monocyte-derived microparticles bind to activated platelets in an interaction mediated by platelet P-selectin and microparticle PSGL-1. We propose that PSGL-1 plays a role in blood coagulation in addition to its known role in leukocyte trafficking

Accumulation of Tissue Factor into Developing Thrombi In Vivo Is Dependent upon Microparticle P-Selectin Glycoprotein Ligand 1 and Platelet P-Selectin

Using a laser-induced endothelial injury model, we examined thrombus formation in the microcirculation of wild-type and genetically altered mice by real-time in vivo microscopy to analyze this complex physiologic process in a system that includes the vessel wall, the presence of flowing blood, and the absence of anticoagulants. We observe P-selectin expression, tissue factor accumulation, and fibrin generation after platelet localization in the developing thrombus in arterioles of wild-type mice. However, mice lacking P-selectin glycoprotein ligand 1 (PSGL-1) or P-selectin, or wild-type mice infused with blocking P-selectin antibodies, developed platelet thrombi containing minimal tissue factor and fibrin. To explore the delivery of tissue factor into a developing thrombus, we identified monocyte-derived microparticles in human platelet–poor plasma that express tissue factor, PSGL-1, and CD14. Fluorescently labeled mouse microparticles infused into a recipient mouse localized within the developing thrombus, indicating that one pathway for the initiation of blood coagulation in vivo involves the accumulation of tissue factor– and PSGL-1–containing microparticles in the platelet thrombus expressing P-selectin. These monocyte-derived microparticles bind to activated platelets in an interaction mediated by platelet P-selectin and microparticle PSGL-1. We propose that PSGL-1 plays a role in blood coagulation in addition to its known role in leukocyte trafficking