Eldon Puckrin

Passive standoff detection of chemical warfare agents on surfaces

Results are presented on the passive standoff detection and identification of chemical warfare (CW) liquid agents on surfaces by the Fourier-transform IR radiometry. This study was performed during surface contamination trials at Defence Research and Development Canada-Suffield in September 2002. The goal was to verify that passive long-wave IR spectrometric sensors can potentially remotely detect surfaces contaminated with CW agents. The passive sensor, the Compact Atmospheric Sounding Interferometer, was used in the trial to obtain laboratory and field measurements of CW liquid agents, HD and VX. The agents were applied to high-reflectivity surfaces of aluminum, low-reflectivity surfaces of Mylar, and several other materials including an armored personnel carrier. The field measurements were obtained at a standoff distance of 60 m from the target surfaces. Results indicate that liquid contaminant agents deposited on high-reflectivity surfaces can be detected, identified, and possibly quantified with passive sensors. For low-reflectivity surfaces the presence of the contaminants can usually be detected; however, their identification based on simple correlations with the absorption spectrum of the pure contaminant is not possible.

Passive standoff detection of Bacillus subtilis aerosol by Fourier-transform infrared radiometry

An analysis is presented on the passive standoff detection and identification of Bacillus subtilis (BG) clouds with the Compact ATmospheric Sounding Interferometer (CATSI) sensor. This research is based on recent spectral measurements obtained during the Technology Readiness Evaluation trial held July 2002 at Dugway Proving Ground, Utah. Results obtained from three trial BG cloud episodes are used to explain and demonstrate the detection capability of the CATSI sensor. The BG clouds were measured at a distance of 3 km from the sensor in a near-horizontal path scenario. It was found that the low thermal contrast of approximately 0.2 K between the BG cloud and the background yielded weak but observable spectral signatures. The processing of the spectral signatures with the GASeous Emission Monitoring (GASEM) algorithm has provided a rough estimate of BG cloud column densities. The results of a series of simulations with the FASCOD3 transmission model have shown that the detection sensitivity for BG can be greatly improved for both slant path uplooking and downlooking scenarios.

Passive remote monitoring of chemical vapors by differential Fourier-transform infrared radiometry: results at a range of 1.5 km

A method for the passive remote monitoring of chemical vapors by differential Fourier-transform infrared radiometry is presented to determine the characteristics of a chemical vapor plume from a stack located at a distance of more than 1 km from the sensor. This measurement technique is based on the use of a double-beam Fourier-transform infrared spectrometer that is optimized for optical subtraction. A description of the interferometer (compact atmospheric sounding interferometer) is given along with the algorithm (GASEM) that has been developed for the on-line detection, identification, and quantification of chemical vapor plumes. The detection method is described with a particular emphasis placed on its monitoring capabilities. The analysis focuses on the experimental results obtained at a recent open-air experiment for vapor plume mixtures of dimethyl methyl phosphonate and SF6 probed at a distance of 1.5 km. The accuracy of a simplified plume radiance model implemented in the detection algorithm is specifically addressed. The measurement technique has been successfully used to detect and identify low, medium, and high concentrations of vapor mixtures but appears to have limited quantification capabilities in its present form.

Diurnal emissivity dynamics in bare versus biocrusted sand dunes

Land surface emissivity (LSE) in the thermal infrared depends mainly on the ground cover and on changes in soil moisture. The LSE is a critical variable that affects the prediction accuracy of geophysical models requiring land surface temperature as an input, highlighting the need for an accurate derivation of LSE. The primary aim of this study was to test the hypothesis that diurnal changes in emissivity, as detected from space, are larger for areas mostly covered by biocrusts (composed mainly of cyanobacteria) than for bare sand areas. The LSE dynamics were monitored from geostationary orbit by the Spinning Enhanced Visible and Infrared Imager (SEVIRI) over a sand dune field in a coastal desert region extending across both sides of the Israel-Egypt political borderline. Different land-use practices by the two countries have resulted in exposed, active sand dunes on the Egyptian side (Sinai), and dunes stabilized by biocrusts on the Israeli side (Negev). Since biocrusts adsorb more moisture from the atmosphere than bare sand does, and LSE is affected by the soil moisture, diurnal fluctuations in LSE were larger for the crusted dunes in the 8.7 μm channel. This phenomenon is attributed to water vapor adsorption by the sand/biocrust particles. The results indicate that LSE is sensitive to minor changes in soil water content caused by water vapor adsorption and can, therefore, serve as a tool for quantifying this effect, which has a large spatial impact. As biocrusts cover vast regions in deserts worldwide, this discovery has repercussions for LSE estimations in deserts around the globe, and these LSE variations can potentially have considerable effects on geophysical models from local to regional scales.

Comparison of clear-sky surface radiative fluxes simulated with radiative transfer models

The surface fluxes of several important radiatively active gases, including H2O, CO2, CH4, N2O, O3, and the chlorofluorocarbons CFC11 and CFC12, were simulated with the radiation band models from the National Center for Atmospheric Research (NCAR) community climate model 3 (CCM3), the single-column community atmospheric model (SCAM), and the Canadian global climate model 3 (GCM3). These results were compared with the measured fluxes for a very cold winter day and with the simulated results for other standard atmospheres using the line-by-line radiative transfer model (LBLRTM). The comparison shows that the total surface radiative flux contributed by all the greenhouse gases combined is well simulated by the SCAM and GCM3 radiation band models. The two models generally agree within about 1% of the line-by-line result for all the atmospheric conditions studied. The error in the total flux simulated by the older CCM3 code, however, can be as large as 7% depending on the atmospheric conditions. The SCAM code consistently models H2O better than the CCM3 and GCM3 codes, typically displaying errors of less than 1 W/m2 for all atmospheric conditions. All of the models have difficulty in modelling accurately the radiative flux of CH4 and N2O. In general, the inaccuracy increases, by as much as 200% in some cases, as the amount of H2O in the atmosphere increases. The source of the problem appears to be related to the overlapping bands of other gases. The error in the ozone flux varies from 5% to 15% for the CCM3 and SCAM models, and it can be as large as 30% for the GCM3 code. The CCM3 and SCAM models simulated the chlorofluorocarbon fluxes to within 0.06 W/m2, but this leads to relative errors of 20%–40% for the various atmospheric scenarios. The errors for the CFCs are even larger in the case of the GCM3 model.

Airborne infrared hyperspectral imager for intelligence, surveillance and reconnaissance applications

Persistent surveillance and collection of airborne intelligence, surveillance and reconnaissance information is critical in today’s warfare against terrorism. High resolution imagery in visible and infrared bands provides valuable detection capabilities based on target shapes and temperatures. However, the spectral resolution provided by a hyperspectral imager adds a spectral dimension to the measurements, leading to additional tools for detection and identification of targets, based on their spectral signature. The Telops Hyper-Cam sensor is an interferometer-based imaging system that enables the spatial and spectral analysis of targets using a single sensor. It is based on the Fourier-transform technology yielding high spectral resolution and enabling high accuracy radiometric calibration. It provides datacubes of up to 320×256 pixels at spectral resolutions as fine as 0.25 cm-1. The LWIR version covers the 8.0 to 11.8 μm spectral range. The Hyper-Cam has been recently used for the first time in two compact airborne platforms: a bellymounted gyro-stabilized platform and a gyro-stabilized gimbal ball. Both platforms are described in this paper, and successful results of high-altitude detection and identification of targets, including industrial plumes, and chemical spills are presented.

Passive Standoff Detection of SF6 at a Distance of 5.7 km by Differential Fourier Transform Infrared Radiometry

Recent results are presented on the passive detection, identification, and quantification of a vapor cloud of SF6 measured at a horizontal standoff distance of 5.7 km using a dual-beam interferometer optimized for background signal suppression. The measurements were performed at Defense Research and Development Canada (DRDC)–Valcartier during a number of recent open-air experiments. The measurement approach is based on the differential passive standoff detection method that has been developed by DRDC Valcartier during the past few years. This work represents the first such measurement reported in the open literature for a standoff distance as large as 5.7 km. These results clearly demonstrate the capability of the differential radiometry approach to the detection, identification, and quantification of chemical vapor clouds located at long distances from the sensor.

Airborne infrared hyperspectral imager for intelligence, surveillance, and reconnaissance applications

Persistent surveillance and collection of airborne intelligence, surveillance and reconnaissance information is critical in todays warfare against terrorism. High resolution imagery in visible and infrared bands provides valuable detection capabilities based on target shapes and temperatures. However, the spectral resolution provided by a hyperspectral imager adds a spectral dimension to the measurements, leading to additional tools for detection and identification of targets, based on their spectral signature. The Telops Hyper-Cam sensor is an interferometer-based imaging system that enables the spatial and spectral analysis of targets using a single sensor. It is based on the Fourier-transform technology yielding high spectral resolution and enabling high accuracy radiometric calibration. It provides datacubes of up to 320×256 pixels at spectral resolutions as fine as 0.25 cm-1. The LWIR version covers the 8.0 to 11.8 μm spectral range. The Hyper-Cam has been recently used for the first time in two compact airborne platforms: a belly-mounted gyro-stabilized platform and a gyro-stabilized gimbal ball. Both platforms are described in this paper, and successful results of high-altitude detection and identification of targets, including industrial plumes, and chemical spills are presented.

Standoff detection of explosives: a challenging approach for optical technologies

Standoff detection of explosives residues on surfaces at few meters was made using optical technologies based on Raman scattering, Laser-Induced Breakdown Spectroscopy (LIBS) and passive standoff FTIR radiometry. By comparison, detection and analysis of nanogram samples of different explosives was made with a microscope system where Raman scattering from a micron-size single point illuminated crystal of explosive was observed. Results from standoff detection experiments using a telescope were compared to experiments using a microscope to find out important parameters leading to the detection. While detection and spectral identification of the micron-size explosive particles was possible with a microscope, standoff detection of these particles was very challenging due to undesired light reflected and produced by the background surface or light coming from other contaminants. Results illustrated the challenging approach of detecting at a standoff distance the presence of low amount of micron or submicron explosive particles.

Airborne infrared-hyperspectral mapping for detection of gaseous and solid targets

Airborne hyperspectral ground mapping is being used in an ever-increasing extent for numerous applications in the military, geology and environmental fields. The different regions of the electromagnetic spectrum help produce information of differing nature. The visible, near-infrared and short-wave infrared radiation (400 nm to 2.5 μm) has been mostly used to analyze reflected solar light, while the mid-wave (3 to 5 μm) and long-wave (8 to 12 μm or thermal) infrared senses the self-emission of molecules directly, enabling the acquisition of data during night time. The Telops Hyper-Cam is a rugged and compact infrared hyperspectral imager based on the Fourier-transform technology. It has been used on the ground in several field campaigns, including the demonstration of standoff chemical agent detection. More recently, the Hyper-Cam has been integrated into an airplane to provide airborne measurement capabilities. The technology offers fine spectral resolution (up to 0.25 cm-1) and high accuracy radiometric calibration (better than 1 degree Celsius). Furthermore, the spectral resolution, spatial resolution, swath width, integration time and sensitivity are all flexible parameters that can be selected and optimized to best address the specific objectives of each mission. The system performance and a few measurements have been presented in previous publications. This paper focuses on analyzing additional measurements in which detection of fertilizer and Freon gas has been demonstrated.