passive standoff detection of chemical warfare agents on surfaces

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assive standoff detection of chemical warfaregents on surfaces

ean-Marc Theriault, Eldon Puckrin, Jim Hancock, Pierre Lecavalier,armela Jackson Lepage, and James O. Jensen

Results are presented on the passive standoff detection and identification of chemical warfare �CW� liquidagents on surfaces by the Fourier-transform IR radiometry. This study was performed during surfacecontamination trials at Defence Research and Development Canada–Suffield in September 2002. Thegoal was to verify that passive long-wave IR spectrometric sensors can potentially remotely detectsurfaces contaminated with CW agents. The passive sensor, the Compact Atmospheric Sounding In-terferometer, was used in the trial to obtain laboratory and field measurements of CW liquid agents, HDand VX. The agents were applied to high-reflectivity surfaces of aluminum, low-reflectivity surfaces ofMylar, and several other materials including an armored personnel carrier. The field measurementswere obtained at a standoff distance of 60 m from the target surfaces. Results indicate that liquidcontaminant agents deposited on high-reflectivity surfaces can be detected, identified, and possiblyquantified with passive sensors. For low-reflectivity surfaces the presence of the contaminants canusually be detected; however, their identification based on simple correlations with the absorptionspectrum of the pure contaminant is not possible. © 2004 Optical Society of America

OCIS codes: 120.0280, 120.5630, 120.6200, 280.0280, 300.0300, 300.6340.

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. Introduction

hemical warfare �CW� agents such as mustard �HDr bis �2-chloroethyl� sulfide� and VX �O-ethyl-S-�2-iisopropylaminoethyl� methylphosphonothiolate� areecognized as serious threats by the defense commu-ity. These agents, characterized by moderate to

ow vapor pressures, can readily be deposited on sur-aces, creating hazardous health conditions.

Current reconnaissance systems normally employoint detectors that are based on techniques involv-ng ion-mobility spectrometry, flame photometry, dyeolubility, or enzymatic reactions to detect CW con-amination on surfaces. There are some active sys-ems based on the lidar technique that are currentlyeing developed to measure surfaces contaminated

J.-M. Theriault �[email protected]� and E.uckrin are with Defence Research and Development Canada–alcartier, 2459 Pie XI Boulevard North, Val-Belair, Quebec, Can-da G3J 1X5. J. Hancock, P. Lecavalier, and C. J. Lepage areith Defence Research and Development Canada–Suffield, P.O.ox 4000, Station Main, Medicine Hat, Alberta, Canada T1A 8K6.. O. Jensen is with the United States Army Soldier and Biologicalhemical Command, AMSSB-RRT-Domestic Preparedness, Aber-een Proving Ground, Maryland 21010-5424.Received 17 December 2003; accepted 20 April 2004.0003-6935�04�315870-16$15.00�0

s© 2004 Optical Society of America

870 APPLIED OPTICS � Vol. 43, No. 31 � 1 November 2004

ith CW agents.1,2 However, lidar systems have annherent attribute in that their laser source can act as

beacon, which is often not desirable. Some workn detection of surface contaminants has also beenarried out with IR lasers3,4 and laser-induced vapor-mission techniques.5 Long-wave infrared �LWIR�pectrometric sensors, such as the M21—RSCAALremote-sensing chemical agent alarm� have beensed in the field for passive standoff detection ofhemical-vapor clouds. Preliminary measurementsnd analyses suggest that passive LWIR spectromet-ic sensors have the potential to remotely detect sur-ace contaminants with the reflected radiance of theold sky. These types of sensor would be highly suit-ble for situations of contamination avoidance thatequire the ability to remotely monitor large areas oferrain in real time with ground-based and airbornelatforms, such as aircraft, helicopter, or unmannederial vehicles. Such a rapid remote-monitoring ca-ability on surface terrains would provide a signifi-ant advantage in the event of a CW attack.

For the past few years Defence Research and De-elopment Canada �DRDC�–Valcartier has been in-estigating the application of passive standoffetection by Fourier-transform infrared �FTIR� radi-metry to the problem of surface contamination byW agents. The principal sensor developed for pas-
ive standoff detection by DRDC Valcartier is the

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ual-beam compact atmospheric sounding inter-erometer �CATSI�. Preliminary measurements onimulants have shown that passive detection of liquidontaminants on surfaces is feasible with LWIRpectrometers.6–8

The CATSI system was deployed at the surfaceontamination �SURFCON� trial for the passivetandoff detection of real surface-agent contami-ants, which was held at DRDC Suffield, 22–27 Sep-ember 2002. In this paper we summarize theassive standoff results obtained with the CATSIensor for CW agents HD and VX on contaminatedurfaces in laboratory and field conditions. Therinciples and the phenomenology associated withassive standoff detection of surface contaminantsre also reviewed along with a description of theATSI passive sensor.

. Detection Principles and Phenomenology

. Modeling Surface Contaminant Radiance andeflectance

passive LWIR standoff sensor functions by ex-loiting the temperature differences ��T� that existetween a chemical cloud and the backgroundcene. When a liquid contaminant is present on aurface, no temperature difference exists betweenhe contamination and the substrate �or surface�,ut �T does exist between the contaminated surfacend the cold sky, providing a high surface-to-skyemperature contrast that yields favorable detec-ion possibilities. Similarly, if the radiation fromn external hot or cold source is reflected from theurface, it is possible to observe the spectrum of theontaminant.The radiative transfer intervening at a surface

an be understood from simple physical arguments.igure 1 shows a diagram and defines the parame-ers used to evaluate the radiance originating fromlean and contaminated surfaces exposed to an out-oor environment. For a clean surface with reflec-

ig. 1. Schematic diagram and the parameters used to evaluatehe radiance of a clean surface and a surface covered by a contam-nant.

ance R0 the spectral radiance measured by the i

ensor contains two components, i.e., the emittedadiance from the surface B�1 � R0� and the coldky radiance reflected by the surface LdownR0. Thearameter Ldown represents the downwelling radi-nce from the sky, and B is the Planck radiancevaluated at the temperature T of the surface and isiven by

B � � C1�3

exp�C2�

T � � 1� , (1)

here C1 and C2 are constants with values of 1.191 �0�12 W cm2 and 1.439 cm K, respectively, � is theave number in cm�1, and B is in W��cm2 sr cm�1�.dding the two radiance components, B�1 � R0� anddownR0, yields an expression for the radiance of thelean surface that is given by

Lclean � B � R0�B � Ldown�. (2)

Similarly, for a contaminated substrate with a re-ectance Rcont, as shown in Fig. 1, the spectral radi-nce measured by the sensor is given by

Lcont � B � Rcont�B � Ldown�. (3)

quantity of interest for studying the perturbationffects of a contaminant on a surface is the differen-ial spectral radiance ��L�, i.e., the radiance changeLcont � Lclean� obtained by subtracting Eq. �2� fromq. �3�:

Lcont � Lclean � �L � �R0 � Rcont��B � Ldown�. (4)

nspection of Eq. �4� reveals some simple facts con-erning the sensitivity for detecting contaminants byassive spectral radiometry. First, the radiancehange is proportional to the reflectance contrastR0 � Rcont�, indicating that a highly reflecting sur-ace, such as a metallic plate, offers more sensitivityor detection. Second, the radiance change is pro-ortional to the radiative contrast between thelanck surface radiance and the downwelling skyadiance �B � Ldown�. Since the downwelling radi-nce increases with cloud cover, which in turn resultsn a decrease in radiative contrast, the best detectionossibilities are obtained in clear sky conditions.To illustrate detection of surface contaminants by

assive spectral radiometry, the differential radiancepectra ��L�, as shown in Fig. 2, were computed withgeneric model for 1 g�m2 of VX deposited on sur-

aces of high and low reflectivity. For these calcula-ions the surface temperature was fixed at 10 °C andhe downwelling radiance Ldown, was simulated withblackbody radiance at temperatures typical of the

ky. In Fig. 2�a� two sky temperatures ��30 °C and5 °C� were used to compute the differential radi-nce for the contaminant deposited on a high-eflectivity surface with R0 0.95. It is evident thathe differential radiance associated with the stron-est surface-to-sky temperature contrast �i.e., 40 °C�
s approximately an order of magnitude greater than
1 November 2004 � Vol. 43, No. 31 � APPLIED OPTICS 5871

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hat obtained with a surface-to-sky temperature con-rast of 5 °C. Figure 2�b� shows similar calculationsor a low-reflectivity surface with R0 0.05. In thisase the spectral radiance signature of VX is approx-mately 20 times smaller than for the high-eflectivity surface, but it can still be detected for atrong surface-to-sky temperature contrast �40 °C�.or the case of little temperature contrast �5 °C� the

ntensity of the VX radiance signature approacheshe noise level of a typical sensor �1 � 10�8 W��cm2 srm�1� at a resolution of 4 cm�1� and would be barelyetectable. These generic results qualitatively illus-rate the fact that high-reflectivity surfaces andtrong surface-to-sky temperature contrasts favorhe detection and identification of contaminants byassive spectral radiometry.For the analysis of the experimental results it is

onvenient to express the differential radiance in Eq.4� in terms of the clean-surface radiance Lclean ratherhan the downwelling sky radiance Ldown, which can-ot be easily measured with a sensor that is config-red for surface measurements. Therefore the

ig. 2. Differential radiance spectra computed with a genericodel for 1 g�m2 of VX deposited on the surface: �a� high-

eflectivity surface �0.95�; �b� low-reflectivity surface �0.05�.

xpression for Ldown obtained from Eq. �2� can be l


ubstituted into Eq. �4� to yield the differential radi-nce in the form

�L � �1 �Rcont

R0��B � Lclean�. (5)

Another quantity of interest in the analysis of thexperimental results is the surface-reflection ratio ofhe contaminated-versus-clean surface �Rcont�R0�hat can be estimated from the measured �L andclean by inversion of Eq. �5�, i.e.,

Rcont

R0� 1 � � �L

B � Lclean� . (6)

Equations �5� and �6� form the basic set of expres-ions used to derive the spectral radiance and re-ectance properties from the measurementserformed at the SURFCON trial on surfaces con-aminated with liquid agents. In the data-cquisition procedure with CATSI there were twouccessive recording steps. First, the spectrum ofhe clean surface Lclean was recorded, calibrated,nd then stored. Second, after application of theurface contaminant, CATSI was used in the differ-ntial mode to provide on-line subtraction betweenhe radiance from the contaminated surface Lcontnd the previously recorded radiance from the cleanurface Lclean, which yielded the differential radi-nce �L. Both recorded quantities, Lclean and �L,ere incorporated into Eq. �6� to obtain the

pectral-reflectance ratio from the CATSI data.he Planck radiance B was evaluated based on theeasured surface temperature.

. Inhomogeneous-Layer Reflectance Model

he analysis of surface-reflectance properties mea-ured at the SURFCON trial has prompted devel-pment of a simple model, referred to as thenhomogeneous-layer �IL� model, which quantita-ively links the surface reflectance to the contami-ant coverage. This model is relevant for the case

n which the sensor probes relatively large areasontaining many smaller islands of contaminant.igure 3 shows typical distribution patterns of con-aminant agents deposited on an aluminum platend a Mylar sheet. It is evident that even afterniform application the agent tends to aggregatend form small islands. The shapes of the islandsre quite variable with diameters as large as 1 cm.he level of inhomogeneity varies with the agent,he surface type, and the surface coverage, but over-ll only a few samples appear by visual inspectiono be marginally uniform.

To develop the theory for the IL model, it is neces-ary first to consider reflection from a homogenous
ayer on a substrate, as shown in Fig. 4�a�. For this

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ituation the reflectance of the contaminated surfacecont is given by9

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2

1 � RiRS�2 , (7)

here � is defined as the single-pass transmission ofhe film layer and RS and Ri are the reflectances ofhe air–agent interface and the agent–surface inter-ace, respectively. For the practical measurementlans discussed below the value of the reflectancerom the air–contaminant interface RS is expected toe in the range of 4%–6%. This small value of re-ectance is typical of many liquids. Thus, in thearticular case of a liquid contaminant on a high-eflectivity surface, if it is assumed that RS is zero,he contaminated surface reflectance given by Eq. �7�s well approximated by

Rcont � R0�2, (8)

here R0 is the reflectance of the clean high-eflectivity surface. The surface coverage may bealculated from the ratio of the reflectivities of theontaminated and clean surfaces, assuming that

ig. 3. Nonuniform distribution of the mustard agent on �a� anluminum plate and �b� a Mylar sheet.

he contaminant film attenuates the incident radi- n

tion according to Beer’s law. After normalizationo the clean-surface reflectance, Eq. �8� becomes

Rcont

R0� �2 � exp��2k�L�, (9)

here k is the absorption coefficient of the contami-

ig. 4. Diagram and parameters used to evaluate the reflectancef �a� a homogeneous layer of an agent deposited on a surface, �b�n inhomogeneous layer of an agent deposited on a surface, and �c�diagram illustrating the three consecutive measurements asso-

iated with characterization of the agent, AG, deposited on the

ant and �L is the surface coverage �in units of grams


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er square meter or equivalent�. In practice the sur-ace coverage can be determined by a least-squares fito the measured spectral-reflectivity ratio by using aodified Beer’s law expression

Rcont

R0� �0 exp��2k�L�, (10)

here �0 is an empirical fit parameter that accountsor broadband scattering losses in the contaminant.

The reflectance from an inhomogeneous contami-ated surface is found by a simple extension of thexpressions derived above for the homogeneous layerodel. The IL model geometry is represented and

he associated parameters are defined in Fig. 4�b�.he agent on the surface is represented by a distri-ution of small aggregates. In the IL model the ef-ective reflectance Rcont is defined as the weightedverage of the reflectance R0 originating from thencovered part of the surface and the portion coveredith the agent. By extension of Eq. �9� it follows

hat the effective reflectance ratio of an inhomoge-eous layer of the agent deposited on a high-eflectivity surface is given by

Rcont

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2 (11)

r alternatively

Rcont

R0� f0 � f1 exp��2k�L�, (12)

here f0 is arbitrarily defined as the filling factor ofhe uncovered part of the surface and f1 is the fillingactor of the agent times a scattering loss factor �bynalogy with Eq. �10��. Since f1 includes the scat-ering loss, the sum of f0 f1 is smaller than unity.n practice f0, f1 and the surface coverage ��L� areetermined by using a three-parameter fit proceduren the measured spectral radiance ratio �Rcont�R0�.For the case of the low-reflectivity surfaces no at-

empt was made to fit the data owing to the lack ofnformation contained in the spectrum of the reflec-ance ratio. For these cases the experimental re-ults have been analyzed only from a qualitativeoint of view.

. Agents on Transmitting Surfaces

o measure the IR signature of the agent by trans-ission as well as by reflection, a transmitting Mylar

lm was used as a substrate, which was backed by anluminum plate. In this case a specific approach isecessary to characterize the properties of the cleannd the contaminated substrate. The reflected ra-iation contains not only a contribution from the tar-et substrate but also the radiation reflected by thenderlying background plate. Figure 4�c� illus-rates the ray tracing of the reflected radiation asso-iated with the clean and the agent-covered Mylarubstrate in the optical assembly. In both cases the
adiation from the underlying plate is probed by the i

assive sensor. Thus the differential radiance mea-urements represent the reflectance of the clean andhe contaminated optical assemblies rather than theurface alone. Hence the objective is to detect thepectral signature of the surface contaminant fromhe comparison of the reflectances associated withhe clean �RMy� and the contaminated �Rcont� assem-lies. This was accomplished from a sequence ofhree consecutive radiance measurements, summa-ized in Fig. 4�c�, taken to characterize the surfaceroperties associated with the clean and the agent-ontaminated Mylar sheet. First, the radianceclean of the aluminum plate �reflectance R0� was re-orded and stored as a reference measurement. Sec-nd, the Mylar holder was mounted directly abovehe aluminum plate, and a differential radiance mea-urement �radiance from Mylar sheet LMy minus pre-iously recorded Lclean� was taken of the clean Mylarheet. Finally, the contaminated Mylar wasounted directly above the aluminum plate exactly

n the same configuration as for the clean Mylarheet, and a differential radiance measurement �ra-iance from contaminated Mylar sheet Lcont minusreviously recorded Lclean� was obtained of the con-aminated Mylar. From these radiance measure-ents the effective reflectance ratios corresponding

o the clean Mylar assembly �RMy�R0� and the agent-overed Mylar assembly �Rcont�R0� can be evaluatedased on analogous expressions of Eq. �6�, i.e.,

RMy

R0� 1 � � �LMy

B � Lclean� , (13a)

Rcont

R0� 1 � � �Lcont

B � Lclean� , (13b)

here �LMy and �Lcont are the differential radiancesssociated with the clean and the contaminated My-ar sheet above an aluminum sheet, respectively; i.e.,

�LMy � LMy � Lclean, (14a)

�Lcont � Lcont � Lclean. (14b)

ince an aluminum plate was present as the back-round, the reflectance ratios given by Eqs. �13a� and13b� are referenced to the reflectance R0 of the alu-

inum plate.

. CATSI Sensor

he CATSI instrument is an FTIR spectrometer thatakes advantage of the differential detection capabilityrovided by a symmetrical dual-beam inter-erometer.10–12 For this system two beams of ther-al radiation originating from different scenes can

e combined onto a single detector and subtractedptically in real time. Thus, if one beam enteringhe interferometer corresponds to the radiance from aontaminated surface and the other corresponds tohe radiance from a similar uncontaminated �clean�urface, the resulting differential spectrum corre-ponds primarily to the IR signature of the contam-
nant.

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The CATSI system consists of two identical New-onian telescopes with diameters of 10 cm that areptically coupled to the dual-beam interferometer.igure 5�a� shows the instrument mounted on a tri-od together with a schematic diagram �Fig. 5�b��here the instrument’s optical design is summarized.he specifications of the CATSI system are as follows:

he scene field of view from 4 to 11 mrad, spectraloverage from 7 to 13 m, and a maximum spectralesolution of 1 cm�1. A flat-plate mirror placed inront of each telescope can be rotated to the selectedcene. The pointing capability of this scene mirrorermits azimuth measurements to be made from 0 to80 deg. Coarse adjustments in azimuth and eleva-ion are simply achieved by rotating the whole as-embly. After reflection from the scene mirror thenput beam is focused by the Newtonian telescope athe entrance of the interferometer and then reflectedy an off-axis parabolic mirror to produce a colli-ated beam of proper diameter that impinges on the

ig. 5. �a� CATSI sensor with the optical head mounted on aripod; �b� associated optical diagram.

eam splitter. w

A double-pendulum scanning mechanism �Fig.�b�� controls the periodic displacement of the twoorner-cube reflectors, CC, that generate the inter-erogram. The beam splitter, BS, consists of a thinir gap squeezed between two ZnSe substrates withntireflection coatings on their external faces. Onlyne of the two available output channels is used athis moment. This output module contains a para-olic and condensing mirror that focuses the radia-ion beam onto a mercury cadmium telluride detector1 mm�, MCT, mounted on a microcooler. The de-ector is specifically optimized for the 7–13- m ther-al IR band. Two CCD cameras mounted on top of

he two telescope modules are used to view the scenesnder consideration.For the SURFCON 2002 trial the CATSI systemas operated either in the differential-detectionode or in the direct-detection mode, which was ob-

ained by blocking one of the two input telescopes.he mode of operation was chosen according to con-traints of the observed scene. All the laboratoryeasurements were performed in the direct-

etection mode with a single telescope, and most ofhe field measurements were performed in theifferential-detection mode by using two telescopes.

. Experimental Procedure

. Laboratory Configuration and Measurement Procedure

wo measurement plans were addressed during theaboratory segment of the SURFCON trial. For therst measurement plan, CW agents were depositedn a smooth aluminum plate that acted as a high-eflectivity surface. For the second measurementlan, a Mylar sheet 76.2 m thick was used as aow-reflectivity surface. Both types of surface had aelatively high surface smoothness that was suitableor the agent characterizations, and they were botheadily available for the experiment. One reason forsing low- and high-reflectivity surfaces was the pos-ibility of estimating the complex index of refractionn and k� of the CW agents. In principle the absorp-ion coefficient k can be derived from the radianceeasured from the agent deposited on the high-

eflectivity surface, whereas the refractive index nan be estimated from the radiance of the agent de-osited on the low-reflectivity surface. However, forost of the measurements performed in this experi-ent the nonuniformity of the agents themselves

hat were deposited on both types of surface inhibitedroper assessment of the complex refractive index.Figure 6 shows the experimental configurationounted in the Canadian National Single Small-cale Facility at DRDC Suffield. A cryogenic black-ody fabricated from black anodized aluminum andeasuring 46 � 46 cm acted as a cold source to sim-late the downwelling sky radiance. A dry ice andcetone mixture was used to provide an effectivelackbody temperature of approximately �40 °C to50 °C, even with an ice layer present. The alumi-um plate �target�, or alternatively a Mylar sheet,
as mounted on an adjustable stage that allowed the

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late to be rotated in the x and y planes. The agentas applied at a known volume with a disposableipet and spread with a foam applicator. Contami-ation densities �also referred to as surface coverage�anged from 0.25 to 10 g�m2, depending on the agentnder study. Figure 6 also illustrates the opticalaths between the source and the CATSI sensor inhe laboratory experimental configuration. The ra-iation emitted from the cold blackbody first im-inged on the target aluminum plate �or Mylar sheet�hrough a large folding mirror. The cold blackbodyadiance was then subsequently reflected back to theATSI sensor through the folding mirror. In Fig. 7

ig. 6. Ray tracing of thermal radiation for the experimentaletup.

ig. 7. Five successive steps of measurements for obtaining theadiance properties of the contaminant agent on a Mylar sheet

uubstrate and on an aluminum-plate substrate.


he five successive steps for obtaining the radianceeasurements are summarized. Two referenceeasurements of the reflectance from the clean alu-inum plate were made in each sequence to ensure

ood reproducibility. These measurements of refer-nce and target radiance were processed to evaluatehe differential radiances and the reflectance proper-ies associated with the clean and the contaminatedurfaces. Once the experimental sequence was com-leted, the plate was decontaminated and a new plateas positioned in the stage before starting the next

equence of measurements.

. Field-Trial Configuration and Measurement Procedure

wo types of experiment were performed for the fieldortion of the SURFCON trial. The first involvedcquisition of the IR signatures of CW agents on sur-aces of aluminum, sod, concrete, and white andreen painted panels. The second experiment in-olved acquisition of the IR signatures of CW agentseposited on an armored personnel carrier �APC� ofhe Canadian forces.

Targets of aluminum, sod, concrete, and paintedanels measuring 1 m � 1 m were mounted on aolder at an angle of 45 deg to the ground. Theerimeter of an area that measured 0.5 m � 0.5 mas marked on the target, and an agent with anown volume was applied to this region with a dis-osable pipet and spread with a foam applicator.he agents were applied in an undiluted state to theluminum plate, whereas in the case of the concrete,od, and panel targets the agents were diluted 1:100n diethyl ether. Contamination densities �or sur-ace coverage� were in the range of 0.25–10 g�m2.nce the experimental sequence was completed, thelate was decontaminated and a new plate positionedn the stage before starting the next sequence of mea-urements. Figure 8 shows the different surfaceamples addressed in this study, i.e., the target andhe reference aluminum plates �Fig. 8�a��, the sodamples �Fig. 8�b��, the green painted metal panelsFig. 8�c��, the white painted metal panels �Fig. 8�d��,nd the concrete block sample �Fig. 8�e��. The con-aminated and clean reference plates were mountedpproximately 1.5 m apart from each other on theame type of holder with the same physical orienta-ion. For the differential radiance measurementsith CATSI, one of the telescopes was aimed at the

ontaminated surface and the other was pointed athe clean surface. The sensor was placed outsidehe hazard zone approximately 60 m from the targets.t this distance the field of view of the instrumentpproximately matched the size of the contaminatedrea.In the case of the APC experiment the perimeter of

n area measuring 0.5 m � 0.5 m was marked on theide and front of the APC. The contaminant agentas applied as before with densities ranging from.25 to 10 g�m2. The CATSI sensor measured theifferential radiance by probing both the contami-ated and uncontaminated areas on the APC. Fig-
re 9 shows the hazard zone with the APC as

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bserved from the CATSI sensor site. On-site me-eorological observations of wind speed and direction,ir temperature, humidity, visibility, and sky condi-ions were recorded every 30 min at a meteorologicaltation at DRDC Suffield.

. Laboratory Results and Analyses

. VX and HD Agents on High-Reflectivity SurfacesAluminum Plate�

n all, 12 different measurements were performedver a one-day period by using three contaminantgents that included HD, munitions grade HD, andX with surface coverages ranging from 1 to 10 g�m2.Figure 10�a� shows differential radiance spectraeasured at a resolution of 8 cm�1 for two coverages

f VX on an aluminum plate, and for comparison Fig.

ig. 8. Different target and reference surface samples: �a� alumetal panels, �e� concrete sample.

inum plates, �b� sod, �c� green painted metal panels, �d� white painted

0�b� shows the absorption coefficient of VX obtained e

ig. 9. Hazard zone as observed from the CATSI sensor sitehowing the APC and the associated regions of contaminant cov-
rage.

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rom the signature compilation of Flanigan.13 Theseful spectral domain covered with CATSI ranges

rom 750 to 1450 cm�1 �7–13 m�. The results inig. 10 show that all the spectral features of theeference spectrum are present in the measured spec-ra. It is clear that the spectral signature of VXeposited on aluminum plates can be detected anddentified for surface coverages of 1 and 3 g�m2.

Figure 11 shows the spectral-reflectance ratio �Eq.6�� derived from the CATSI data for VX deposited onn aluminum plate compared with the best-fit calcu-ations obtained with the IL model described by Eq.12�. The fitting parameters include the fraction ofhe uncovered part of the surface f0, the fraction ofhe agent-covered surface times a scattering loss fac-or f1, and the local surface coverage �L.

Results of the three-parameter fits obtained byatching the measured reflectance-ratio spectra toodel calculations are summarized in Table 1. For

he sample with 1-g�m2 average surface coverage theest-fit parameter, f0 0.75, indicated that a largeortion of the surface reflection appeared to come

ig. 10. �a� Differential radiance measured with the CATSI sen-or for two VX coverages deposited on an aluminum plate; �b�bsorption coefficient of VX �for comparison�.

rom uncovered parts of the aluminum plate. Con-


ersely the effective surface coverage of the agent waselatively small as indicated by the small value forhe parameter f1 0.16. The resulting best-fit localoverage was �L 2.1 g�m2. The fact that f0 f1 �signifies that there were some losses from scatter-

ng �approximately 9%�. The fact that the product1 � �L � 1 g�m2 �i.e., 0.34 rather than 1 g�m2�ignifies that the small agent islands were not ran-omly distributed over the surface and that CATSIrobed an area depleted in VX.For the sample with a 3-g�m2 average surface cov-

rage of VX the best-fit parameter, f0 0.17, indi-ated that a relatively small portion of the surfaceeflection appeared to originate from uncovered partsf the aluminum plate. The associated surface cov-rage of the agent was relatively large with a value of1 0.59, and the resulting fit for the local coverageas �L 3.2 g�m2. In this case the scattering loss

f approximately 25% appeared stronger than in therevious case. The product, f1 � �L 1.9 g�m2,epresented approximately two-thirds of the actualverage coverage, and the apparent difference mayell be explained by the scattering loss.Overall the IL model quantitatively reproduced the

eflectance-ratio spectra of VX deposited on the alu-inum plate. However, a sensitivity study per-

ormed on the spectral fit procedure has shown thathe resulting error on the fit parameters may be high.or the two cases presented above the relative errorargin may be as large as 30% for f0 and f1 and 50%

ig. 11. Spectral-reflectance ratio derived from CATSI data forX deposited on an aluminum plate compared with the best-fitalculations obtained with the IL model. Average VX surfaceoverages are 1 and 3 g�m2.

Table 1. Results for VX on Aluminum from the Fit of the IL Model tothe Reflectance-Ratio Spectra Measured by CATSI

Average SurfaceCoverage �g�m2�

FitParameter

f0

FitParameter

f1

Fit LocalCoverage�L �g�m2�

1 0.75 0.16 2.1
3 0.17 0.59 3.2

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or �L. Consequently the current fitting procedurerovides only an estimate of the amount of layer ho-ogeneity based on the three fitting parameters of

he IL model. Other fit procedures should be inves-igated to find ways to reduce the error margin.

Measurements of HD on aluminum were per-ormed for surface coverages of 1, 3, and 10 g�m2.n additional sample corresponding to munitionsrade mustard with a surface coverage of 3 g�m2 waslso investigated. Figure 12�a� shows the differen-ial radiance spectra associated with the four sampleoverages, and, for comparison, Fig. 12�b� shows thebsorption coefficient of HD obtained from the spec-ral signature database of Flanigan.13 All the spec-ral features of HD present in the spectral absorptionoefficient are also evident in the measured spectra ofig. 12�a�.Figure 13 shows the reflectance ratio spectra de-

ived from the CATSI data for HD deposited on anluminum plate compared with the best-fit calcula-

ig. 12. �a� Differential radiance spectra measured with theATSI sensor for four HD coverages deposited on an aluminumlate; �b� absorption coefficient of HD �for comparison�.

ions obtained with the IL model. Since HD is a t

eak absorber, the spectral contrast in the reflec-ance ratio was tenuous. For example, the spec-ral contrast near 1200 cm�1 was 4% for the 1-g�m2

ample, 6.5% for the 3-g�m2 sample, 14% for the-g�m2 ammunition-grade sample, and 13% for the0-g�m2 sample. This indicates that passive spec-ral sensors must be highly sensitive to detect anddentify small amounts of HD on a metallic surface.s expected the spectrum of munitions grade mus-

ard �Fig. 13�c�� was similar to the standard HDpectrum.As observed in Fig. 13 the agreement between theodel calculations of Eq. �12� and the measure-ents is good for all four surface coverages. The

hree-parameter fits where f0, f1, and �L are used toatch the measured reflectance-ratio spectra to theodel calculations are summarized in Table 2.or the four samples the fraction f0 ranged from.68 to 0.77, indicating that a large portion of theurface reflection originated from uncovered partsf the aluminum plate, which also indicated a highevel of inhomogeneity. Conversely the effectiveurface coverage of the agent was relatively small,s indicated by the small values of f1 ranging from.13 to 0.19. The resulting best-fit local coverageL did not seem to follow a simple proportionalityule with the average surface coverage. For exam-le, a local coverage of 3.2 g�m2 was determinedrom the fit for the 1-g�m2 sample, and approxi-ately the same local coverage �3.8 g�m2� was

ound for the 3-g�m2 sample. Such inconsistencyay be explained by the fact that the small con-

aminant agent islands were not randomly distrib-ted over the surface or that CATSI probed an areaepleted or enriched in HD. The same type of in-onsistency was observed by comparing the 3-g�m2

unitions grade sample with the 10-g�m2 sample,here both indicated a local coverage near a valuef 8.5 g�m2. The scattering loss estimated fromhe conservation rule �1 � f0 � f1� for the fouramples ranged from 10% to 15%.Overall the HD signature was clearly detected and

dentified in the differential radiance spectra mea-ured with CATSI. The measured data were consis-ent with the measured absorption coefficient oflanigan.13 The IL model quantitatively repro-uced the reflectance-ratio spectra of HD depositedn an aluminum plate. For the four cases presentedbove the relative error associated with the spectralest-fit procedure was estimated to be better than0% for f0 and f1 and 50% for �L.

. VX and HD Agents on Low-Reflectivity SurfacesMylar Sheet�

Mylar sheet, as shown in Fig. 3�b�, was used fornvestigating CW agents deposited on a low-eflectivity surface. This material was chosen for itsood surface smoothness, high intrinsic rigidity, andow cost. Ideally the Mylar sheet would have beenither totally transparent or totally absorbing in thepectral band of interest �7–13 m�. In both cases
his would have significantly simplified the radiomet-

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Fobtained with the IL model for average surface coverages of �a� 1 g�m2, �b� 3 g�m2, �c� 3 g�m2 �munitions grade�, and �d� 10 g�m2.

5

ic analysis for recovering the spectral signature ofhe agent. However, the Mylar sheet is partiallyransparent and partially opaque in the 7–13- mand, as shown in Fig. 14.In Fig. 4�c� we summarize the sequence of the

hree consecutive radiance measurements taken toharacterize the surface properties associated withhe clean and the agent-contaminated Mylar sheet.irst, the radiance Lclean of the aluminum plate

reflectance R0� was recorded and stored as a refer-nce measurement. Second, the Mylar holder was
ounted directly above the aluminum plate and a
F

10 0.69 0.16 8.8


ifferential radiance measurement �radiance fromhe Mylar sheet LMy minus previously recordedclean� was taken of the clean Mylar sheet. Finally,

ig. 13. Spectral reflectance ratio derived from CATSI data for HD deposited on an aluminum plate compared with best-fit calculations

ig. 14. Double-pass transmission spectrum of a Mylar sheet 76.2

Table 2. Results for HD on Aluminum from the Fit of the IL Model tothe Reflectance-Ratio Spectra Measured by CATSI

Average SurfaceCoverage �g�m2�

FitParameter

f0

FitParameter

f1

Fit LocalCoverage�L �g�m2�

1 0.77 0.13 3.23 0.68 0.17 3.83

�munitions grade�0.69 0.19 8.5

m thick.

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bove the aluminum plate exactly in the same con-guration as for the clean Mylar sheet, and a dif-erential radiance measurement �radiance from theontaminated Mylar sheet Lcont minus previouslyecorded Lclean� of the contaminated Mylar was ob-ained. Figure 15(a) shows the measured differen-ial radiances associated with clean Mylar ��LMy

My � Lclean� and with the Mylar covered with 1 andg�m2 of VX ��Lcont Lcont � Lclean�. From these

adiance measurements the effective reflectance ra-ios corresponding to the clean Mylar assemblyRMy�R0� and the agent-covered Mylar assemblyRcont�R0� were evaluated based on Eqs. 13�a� and3�b�. It is important to emphasize that for bothases �clean and contaminated Mylar� the differentialadiance was generated by using the aluminum-plateadiance as a reference, and consequently the reflec-ance ratios given by Eqs. 13�a� and 13�b� are refer-nced to the reflectance R0 of the aluminum plate.igure 15(b) depicts the reflectance-ratio spectra mea-ured for the clean Mylar assembly and for the Mylar

ig. 15. �a� Examples of measured differential radiance �the referand 3 g�m2 of VX. �b� Measured reflectance-ratio spectra �the rith 1 and 3 g�m2 of VX. �c� Reflectance-ratio spectra �Rcont�RMy

bsorption coefficient of VX �for comparison�.

ssembly covered with 1 and 3 g�m2 of VX. The effect F

f the VX agent tended to reduce the overall effectiveeflectance of the sheet assembly. The fact that bothX surface coverages yielded similar reflectance ratioseems to indicate that the thickness of the agent doesot significantly affect the spectral signature.The effective reflectance of the clean and the con-

aminated assembly, RMy and Rcont, can be under-tood with a simple model based on Fig. 4�c� thatakes into account the two reflectance contributionsuch that

RMy � RS � �S2R0, (15)

Rcont � RScont � �S2�cont

2R0, (16)

here RScont is the reflectance of the agent-coveredylar sheet, �cont is the transmittance of the agent

ayer deposited on the Mylar sheet, and RS and �S arehe reflectance and the transmittance of the cleanylar sheet, respectively. The double-pass trans-ittance spectrum of the Mylar sheet �S

2, shown in

is aluminum plate� for the clean Mylar and for Mylar covered withnce is aluminum plate� for the clean Mylar and for Mylar coveredMylar covered with 1 and 3 g�m2 of VX. The bottom curve is the

enceefere� for

ig. 14, indicates that the transmittance is approxi-


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ately zero in the spectral region greater than 1050m�1. For this region the effective reflectances areiven by the sheet contributions alone �i.e., RMy � RSnd Rcont � RScont�. For the spectral region below000 cm�1 the Mylar sheet transmittance remainsignificant for most of this band.The spectral signature of the agent that we want to

etect and identify manifests itself through the termsScont and �cont in Eq. �16�. Since Mylar also has

everal interfering absorption bands in the 7–13- megion, the agent signature identification becomesather complex. To more readily identify the agent,t is convenient to ratio the agent-contaminated My-ar reflectance measurement Rcont with the clean My-ar reflectance measurement RMy. This results in aartial cancellation of the Mylar spectral signature inhe reflectance measurements. Figure 15(c) showshe reflectance-ratio spectra �Rcont�RMy� measuredor the Mylar sheet covered with 1 and 3 g�m2 of VX.or comparison the bottom curve represents the ab-orption coefficient of VX. The overall effect of theX agent was to reduce the Mylar sheet reflectancey approximately 25%–50% with two exceptions near150 cm�1 and above 1300 cm�1 where the reflec-ance was approximately equal to or greater than thelean Mylar reflectance. The many spectral fea-ures of the reflectance ratio define a signature thatoes not correlate well with the absorption coefficientf VX. A similar result also was found for HD onylar sheets. Many of the spectral features are as-

ociated with the anomalous dispersion in the refrac-ive index of absorbing materials. In this casenowledge of the agent absorption spectrum alone is

nsufficient to explain the effect of the contaminantn a low-reflectivity surface, such as Mylar. A fulluantitative analysis would require knowledge of theefractive index and the absorption coefficient foroth the agent and the underlying substrate.

. Field-Trial Results and Analyses

. VX and HD Agents on Aluminum Plates

or the field measurements obtained with CATSI,hree VX samples deposited on aluminum platesere investigated. The surface coverages associ-ted with these samples were 0.25, 0.5, and 1 g�m2,nd the standoff distance was approximately 60 m.or the three samples the ambient air temperatureas in the range of 9–11 °C. Sunny conditions pre-ailed for the 0.5- and 1-g�m2 samples, and the skyemperature was approximately �48 °C. For the.25-g�m2 sample measurements the sky was cloudynd had a temperature of approximately �15 °C.igure 16(a) shows the differential radiance spectrassociated with the three samples. From the com-arison with the VX absorption coefficient in Fig.0�b�, it is evident that the spectral signature of VXas clearly detected and identified for all coverages.s expected, the 1-g�m2 surface coverage yielded thetrongest signal. Note that even for a relativelymall VX coverage of 0.25 g�m2 a signal greater than
0 times the noise-equivalent spectral radiance of the f

nstrument was observed near the band at 1040m�1. This indicates that relatively small amountsf VX can be easily detected on high-reflectivity sur-aces such as metallic plates.

Figure 16(b) shows the reflectance-ratio spectraRcont�R0� derived from Eq. �6� and the CATSI dataor VX deposited on an aluminum plate. The noisyortions of the spectra higher than 1300 cm�1 wereue to interfering bands from atmospheric speciesuch as H2O, CH4, and N2O. The spectral featuresf VX appearing in the field data of Fig. 16(b) agreeuite well with those from the laboratory data shownn Fig. 11. There was no attempt to quantify theATSI field data with the IL model. However, in-pection of the field spectra indicates that a certainevel of inhomogeneity did exist. For example, the

ig. 16. �a� Differential radiance measured in the field at a stand-ff distance of �60 m with the CATSI sensor for three VX cover-ges deposited on an aluminum plate. �b� Spectral reflectanceatio derived from the CATSI field data for VX deposited on anluminum plate. The VX surface coverages are 0.25, 0.5, and 1�m2.

act that the reflectance ratios of the aluminum

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lates contaminated with 0.25 and 0.5 g�m2 of VXere approximately the same may be attributed togent-clustering effects. An interpretation is that aarge number of small clusters forming the 0.25-g�m2

overage would have approximately the same radio-etric effect as a small number of large clusters form-

ng the 0.5-g�m2 coverage. This type of effect waslso observed in the laboratory data.A similar investigation was made for an HD cov-

rage of 10 g�m2 on the aluminum plate at a standoffistance of approximately 60 m. For this case thembient air temperature was 15.4 °C, and the skyas cloudy with a temperature of approximately31 °C. Figure 17 shows the differential radiance

pectrum associated with the sample. Theeflectance-ratio spectrum �Rcont�R0� derived fromq. �6� and the CATSI data are shown in Fig. 18.rom the comparison with the absorption coefficient

he spectral signature of HD is clearly detected anddentified in Fig. 18. The spectral features of HD

ig. 17. Differential radiance measured in the field at a standoffistance of �60 m with the CATSI sensor for HD deposited on anluminum plate. The HD surface coverage was 10 g�m2.

ig. 18. Spectral reflectance ratio derived from the CATSI fieldata for 10 g�m2 of HD deposited on an aluminum plate: lower

qurve, absorption coefficient of HD �for comparison�.

easured in the field data are fully consistent withhose from the laboratory data �Fig. 13�.

. VX and HD Agents on the Front and Side Surfaces ofn Armored Personnel Carrier

view of the APC with areas marked for agent ap-lication is shown in Fig. 9. Two areas of the APCere selected for the measurements. The side partf the APC was perpendicular to the ground, and theront part formed an angle of approximately 45 degith the ground plane.Two samples of VX deposited on the side surface of

he APC and with surface coverages of 3 and 10 g�m2

ere measured with CATSI. For the 3-g�m2 samplehe ambient air temperature was 11 °C, and the skyas cloudy with a temperature of approximately6.6 °C. For the 10-g�m2 sample the ambient air

emperature was 13 °C, and the sky was cloudy withtemperature of approximately �5.5 °C. Conse-

uently both samples were recorded in approxi-ately the same radiative environmental conditions.igure 19 shows the differential radiance spectra as-ociated with VX deposited on the side surface of thePC. The magnitude of both spectral signals waselatively weak, and the intensity measured for theurface covered with 10 g�m2 of the agent appeared toe 2–3 times stronger than for the 3-g�m2 coverage.igure 20 shows the spectral reflectance ratio derived

rom the CATSI data, and for comparison the bottomurve of Fig. 20 shows the absorption coefficient ofX. The reflectance ratio recorded for the 10-g�m2

ample contained more spectral features, but overallhere was poor correlation with the VX absorptionoefficient spectrum. A similar result was obtainedor HD coverages on the APC. These results areimilar to those obtained for the Mylar substrate,here the spectral features were associated with thenomalous dispersion in the refractive index of ab-orbing materials. A full quantitative analysis re-

ig. 19. Differential radiance spectra measured with CATSI forX surface coverages of 3 and 10 g�m2 deposited on the sideurface of the APC.

uires knowledge of the refractive index and the


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bsorption coefficient for both the agent and the un-erlying substrate consisting of the painted APC.

. VX and HD Agents on Other Surfaces �Concrete, Sod,hite and Green Panels�

here were four other types of surface investigated athe SURFCON field trial. Different surface cover-ges of VX and HD agents were deposited on con-rete, sod, and white and green painted panels ofluminum. All the surfaces were positioned at anngle of 45 deg relative to the ground. One of theetter measurement results was obtained for 3 g�m2

f VX deposited on the white painted panel and for 6�m2 of VX deposited on the green painted panel, ashown in Fig. 21, which represents the differentialadiance measured with CATSI. Both coverages ex-ibited a spectral signature, and the signature asso-iated with the contaminated green panel indicated aelatively high correlation with the VX absorptionoefficient. This is an interesting result that needs

ig. 20. Spectral reflectance ratio derived from CATSI data forX deposited on the APC side surface. The VX surface coveragesre 3 and 10 g�m2. The absorption coefficient of VX is shown foromparison.

ig. 21. Differential radiance measured with CATSI for a VXoverage of 3 g�m2 deposited on a white painted panel and for VXoverage of 6 g�m2 deposited on a green painted panel. The ab-

sorption coefficient of VX is shown for comparison.


urther analysis in terms of the paint’s reflectivity.or all the results involving the other substrates theATSI measurements indicated that a contaminantas present, but its identification was not possibleased on correlation with the absorption coefficient ofhe pure contaminant.

. Summary and Conclusions

detailed investigation has been undertaken withhe CATSI passive sensor for detecting the liquid CWgents HD and VX on a number of surfaces. Mea-urements were obtained in the laboratory and in theeld at the SURFCON trial held September 2002 atRDC Suffield. The laboratory phase of the projectas used to demonstrate the passive detection ofgents on high-reflectivity surfaces of aluminum andow-reflectivity surfaces of Mylar. The CATSI sen-or was used to obtain radiance and reflectance mea-urements of HD and VX on these surfaces. Theest measurements of detection and identification forhese agents occurred for the high-reflectivity sur-aces of aluminum. The good agreement that ex-sted between the measured radiance and thoseimulated with an inhomogeneous-layer model,hich was developed to account for nonuniform sur-

ace coverages, demonstrated that the amount of theurface agent may potentially be quantifiable.Conversely the measurements performed on the

ow-reflectivity surfaces of Mylar indicated that itas possible to detect the presence of a contaminant;owever, the resulting spectral signatures appearedo be more complex to interpret, and the identifica-ion of the agent based solely on the absorption coef-cient of the contaminant was tenuous at best.Field measurements of the liquid contaminants onnumber of surfaces were obtained at a standoff

istance of 60 m. The surfaces being considered in-luded aluminum plates, an APC, concrete, sod, andainted panels. It was possible to detect and iden-ify the HD and VX agents that were applied to theluminum plate in the field. In the case of the HDnd VX agents applied to the surfaces of an APC theATSI sensor showed that contamination wasresent; however, based solely on its spectral absorp-ion coefficient, it was not possible to positively iden-ify the agent. Similar results were obtained foriquid agents on concrete and sod; i.e., the presence of

contaminant was measured, but its identificationas not possible. The deposition of agents onainted aluminum panels yielded marginally betteresults in terms of spectral identification.

Many of the spectral features measured for con-aminants on a low-reflectivity Mylar surface exhib-ted characteristics associated with anomalousispersion in the refractive index of absorbing mate-ials. In this case knowledge of the agent-bsorption spectrum alone is insufficient to explainhe effect of the contaminant on the low-reflectivityurface. A full quantitative analysis would requirenowledge of the refractive index and the absorptionoefficient for both the agent and the underlying sub-
trate. However, in this study the experimental de-

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ermination of the refractive index based on ouradiance measurements of the agents was hinderedy the fact that there were major uncertainties inhe layer homogeneities. Methods for accuratelyeasuring the refractive index of surfaces and con-

aminants should be investigated in the future.hese parameters are needed to accurately modelhe spectral signatures and consequently the sensorerformances for a wide variety of operational mea-urement plans.

The trial on the passive standoff detection of sur-ace contaminants �SURFCON� was held at DRDCuffield, 22–27 September 2002, under the auspicesf The Technical Cooperation Program Chemical, Bi-logical, and Radiological Defence Action Group 46.e thank the scientists and support staff at DRDC

uffield for expertise, leadership, and critical logisti-al support in planning and executing the trial.

eferences1. M. D. Ray, A. J. Sedlacek III, and M. Wu, “Ultraviolet mini-

Raman lidar for standoff, in situ identification of chemicalsurface contaminants,” Rev. Sci. Instrum. 71, 3485–3489�2000�.

2. P. L. Ponsardin, N. S. Higdon, T. H. Chyba, W. T. Armstrong,A. J. Sedlacek III, S. D. Christesen, and A. Wong, “Expandingapplications for surface-contaminants sensing using the laserinterrogation of surface agents �LISA� technique, chemical,and biological standoff detection,” in Chemical and BiologicalStandoff Detection, J. O. Jensen and J-M. Theriault, eds., Proc.SPIE 5268, 321–327 �2004�.

3. S. H. Carlisle, L. W. Carr, V. E. Hatfield, P. L. Holland, D. L.McPherrin, and R. E. Warren, “Advanced algorithm develop-ment for standoff NBC contamination,” CRDEC-CR-107 �U.S.Army Chemical Research, Development, and EngineeringCenter, Aberdeen Proving Ground, Md., June 1991�.

4. J. Leonelli, R. Warren, D. Walter, T. Podoll, D. J. Eckstrom,P. L. Holland, J. M. Moser, S. Boyd, J. E. Jones, J. E. van derLaan, and J. W. Rice, “XD of remote detection of NBC contam-
ination using IR,” ERDEC-CR-108 �Edgewood Research De-
velopment, and Engineering Center, Aberdeen ProvingGround, Md., March 1994�.

5. A. Bell, C. Dyer, and A. C. Jones, “Standoff liquid CW detec-tion, chemical and biological standoff detection,” in Chemicaland Biological Standoff Detection, J. O. Jensen and J.-M. The-riault, eds., Proc. SPIE 5268, 302–309 �2004�.

6. J.-M. Theriault, J. O. Jensen, A. Samuels, A. Ben-David, C.Gittins, and W. Marinelli, “Detection of nonvolatile liquids onsurfaces using passive infrared spectroradiometers,” in Pro-ceedings of the Fifth Workshop on Standoff Detection for Chem-ical and Biological Defense, Williamsburg, Va., 24–28September 2001 �n.p., 2001�, Vol. 5, pp. 1–10.

7. J.-M. Theriault, J. O. Jensen, A. Samuels, A. Ben-David, C.Gittins, and W. Marinelli, “Passive standoff detection of sur-face contaminants: modeling the spectral radiance,” in In-strumentation for Air Pollution and Global AtmosphericMonitoring, J. O. Jensen and R. L. Spellicy, eds., Proc. SPIE4574, 1–10 �2001�.

8. J.-M. Theriault, J. Hancock, J. O. Jensen, E. Puckrin, and F.D’Amico, “Passive standoff detection of liquid surface contam-inants: recent results with CATSI,” in Chemical and Biolog-ical Standoff Detection, J. O. Jensen and J.-M. Theriault, eds.,Proc. SPIE 5268, 1–10 �2003�.

9. F. A. Jenkins and W. E. White, Fundamentals of Optics, 3rd ed.�McGraw-Hill, New York, 1957�, p. 263.

0. J.-M. Theriault, “Modeling the responsivity and self-emissionof a double-beam Fourier-transform infrared interferometer,”Appl. Opt. 38, 505–515 �1999�.

1. J.-M. Theriault, E. Puckrin, F. Bouffard, and B. Dery, “Passiveremote monitoring of chemical vapors by differential FTIRradiometry: results at a range of 1.5 km,” Appl. Opt. 43,1425–1434 �2004�.

2. J.-M. Theriault, E. Puckrin, and J. O. Jensen, “Passive stand-off detection of BG aerosol by FTIR radiometry,” Appl. Opt. 41,6696–6705 �2003�.

3. D. F. Flanigan, “The spectral signatures of chemical agentvapors and aerosols,” CRDC-TR-85002 �U.S. Army ChemicalResearch, Development, and Engineering Center, U.S. ArmyArmament, Munitions and Chemical Command, AberdeenProving Ground, Md., 21005-5066, April 1985� �and personal
communication, 1985�.

passive standoff detection of chemical warfare agents on surfaces

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