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WO2008097262A2 - Passive infrared flir image spectroscopic sensor - Google Patents

Passive infrared flir image spectroscopic sensor Download PDF

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Publication number
WO2008097262A2
WO2008097262A2 PCT/US2007/016040 US2007016040W WO2008097262A2 WO 2008097262 A2 WO2008097262 A2 WO 2008097262A2 US 2007016040 W US2007016040 W US 2007016040W WO 2008097262 A2 WO2008097262 A2 WO 2008097262A2
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WIPO (PCT)
Prior art keywords
interest
emission
intensity
range
spectrum
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PCT/US2007/016040
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French (fr)
Inventor
John Beaty
Charles Dimarzio
Stephen Mcknight
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Northeastern University
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Publication of WO2008097262A2 publication Critical patent/WO2008097262A2/en

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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
    • G01N21/25—Colour; Spectral properties, i.e. comparison of effect of material on the light at two or more different wavelengths or wavelength bands
    • G01N21/31—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry
    • G01N21/35—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light
    • G01N21/3563—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light for analysing solids; Preparation of samples therefor
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
    • G01N21/25—Colour; Spectral properties, i.e. comparison of effect of material on the light at two or more different wavelengths or wavelength bands
    • G01N21/31—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry
    • G01N21/35—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light
    • G01N21/3504—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light for analysing gases, e.g. multi-gas analysis
    • G01N2021/3531—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light for analysing gases, e.g. multi-gas analysis without instrumental source, i.e. radiometric

Definitions

  • Body-worn explosive devices are a growing and important threat to both civilians and the military. Being small, these improvised explosive devices (IEDs) are hidden under the clothing of suicide bombers. Since they are often built out of non-standard parts, these explosives are hard to detect, especially at a safe distance. It is important to develop a sensor suite that can detect whether a person is wearing such an explosive device at sufficient distance to prevent him from entering populated or strategically important areas.
  • IEDs improvised explosive devices
  • Detecting and identifying explosive compounds (or other chemical) at a distance >50 m is the most challenging issue associated with suicide bomb detection.
  • Applicants have developed a concept for a Passive Infrared FLIR Image Spectroscopic Sensor ( ⁇ FLIRISS) that promises to detect and identify explosives (or other chemical compounds) at >50 m.
  • ⁇ FLIRISS Passive Infrared FLIR Image Spectroscopic Sensor
  • the opportunity to survey, detect, and react to a suicide bomber at distances greater than 50 m is substantial. It is estimated the detection limit for ⁇ FLIRISS is approximately 300 ⁇ g/c ⁇ ?. To provide some perspective, a single fingerprint left on a glass slide weighs about 100 ⁇ g, only a factor of three less than the instrument's estimated detection limit.
  • IR infrared
  • Many explosive are sticky, waxy compounds with low vapor pressure.1 They are easily transferred from the bulk explosives to hands, clothing, and equipment, and once they are transferred they stick around for a long time (i.e., months).
  • the proposed detection scheme is based on the assumption that the inside of clothing material is in thermal equilibrium with the wearer's body (37 0 C, or 310 K). The temperature differential between the body and the clothes' surface temperature is assumed to be about 9 0 C. Thus, the clothing can be approximated as a 28 0 C (301 K) blackbody.
  • An integrated system which utilizes the ⁇ FLIRISS system is also disclosed.
  • a combination of four sensor technologies with the ⁇ FLIRISS for explosives detection enables the ability to survey, detect, and react to a suicide bomber at distances greater than 50 m.
  • the presently disclosed concepts are also applicable to suspect vehicles, buildings, and containers.
  • Fig. 1 is a table illustrating properties of various explosives
  • Fig. 2 illustrates an infrared camera and associated elements according to the presently disclosed invention, along with an exemplary image achieved therewith;
  • Fig. 3 illustrates an exemplary bandpass filter curve which can be incorporated into the infrared camera of Fig. 2, along with an exemplary image achieved therewith;
  • Fig. 4 illustrates the basic structure and response of a Fabry-Perot Etalon which can be incorporated into the infrared camera of Fig. 2;
  • Fig. 5 illustrates a detected transmission resulting from use of the infrared camera of Fig. 2 in conjunction with the bandpass filter of Fig. 3 and the Fabry-Perot Etalon of Fig. 4 and exemplary images achieved therewith;
  • Fig. 6 is a graph of radiant excitance through a 100 nanometer bandpass filter
  • Fig. 7 is a graph of the radiant excitance through a 100 nanometer bandpass filter of Fig. 6 in an expanded view
  • Fig. 8 is a graph of spectral radiance plots for the data of Fig. 7;
  • Fig. 9 is a graph of photon counts of the spectra of Fig. 6.
  • Fig. 10 is a graph of the calculated derivative emissivity signal from the source in Fig. 6.
  • Explosives are sticky, waxy compounds with low vapor pressure. Residue is easily transferred from the bulk explosives to hands, clothing, and equipment, and once transferred to a person's clothing, it remains for a long time (e.g., weeks and months) .
  • a human is a blackbody radiator at about 310 K. In the 1 ⁇ m - 12 ⁇ m wavelength spectrum, the intensity of infrared radiation emitted by a human is about 100 times more intense than the reflected ambient light from the sun. Clothing on a human is also at about 300 K and is a radiator, as is any contaminant (e.g., explosives or other chemical compounds) on the clothing.
  • contaminant e.g., explosives or other chemical compounds
  • Explosives are chemical compounds that have specific absorption and emission spectra in the infrared.
  • the functional groups in explosives (or other chemical compounds) resonate (i.e., absorb and emit) at specific infrared wavelengths.
  • FLIR Forward Looking InfraRed
  • Spectral hypercubes consist of X and Y coordinates of pixels from a detector array 12, and ⁇ coordinate in which spectral data are collected. The result is a complete or partial spectrum associated with the image projected on each pixel.
  • a system For the imaging of a person's clothing, a system is utilized to image an area of about 30 x 30 cm 2 (representative of a person's upper torso) via appropriate infrared optics onto a 128 x 128 element focal plane array (FPA) .
  • FPA focal plane array
  • Each of the detector elements measures approximately 30 ⁇ m on edge in one embodiment, for a total array size of about 3.8 x 3.8 /ran 2 .
  • the IR radiation emitted from the target Prior to detection by the FPA, the IR radiation emitted from the target is analyzed by a band-pass filter 18 to prevent order overlap and a tunable etalon filter 20 with a band pass of about 2 cm "1 in the 3100 to 2800 and the 1400 to 900 cm '1 spectral regions.
  • the stains and smudges from explosives exhibit infrared spectral patterns, which are distinctly different from those of the surrounding materials, and can be identified via multivariate methods of analysis.
  • Many explosives e.g., RDX, DEGN, PETN, TNT
  • HMX, MEDINA, EDNA contain amine groups
  • peroxides e.g., TATP
  • acids e.g., Picric acid
  • band pass filter 18 By changing the band pass filter 18 and scanning the Fabry- Perot Etalon 20, the different IR spectral regions can be examined. Many of these characteristic IR vibrational lines lie in the 3 - 5 ⁇ m and 8 - 14 ⁇ m bands of relative atmospheric transparency and are suitable for detection at stand-off ranges on the order of 50 in.
  • Explosives have two physical properties of particular interest. As a class of compounds, they behave like long chain (e.g., C16 n-alkanes) waxes. In addition, and with reference to Fig. 1, they have low vapor pressure and are sticky. These properties are useful if one is looking for the compounds on the surface of clothing. People handling the compounds easily get them on their hands and clothing and the contamination stays on their clothing for weeks or months .
  • all explosive materials are active in infrared wavelengths (i.e., 2 - 15 ⁇ m) and have unique, individual spectra. Many of the compounds contain NO x . Some are ring compounds (i.e., aromatic), while others are peroxides. All of them have identifiable spectra in the 7 - 12 ⁇ m wavelength range and can be identified by their unique spectra.
  • identifying compounds it is preferable to identify multiple resonances or functional groups to improve specificity.
  • infrared spectra are observed by transmitting infrared emission through a sample of a solid mixture, solid or gas.
  • resonance of a molecular vibration or rotation spectra with infrared electromagnetic radiation can also be measured from reflected or emitted radiation.
  • the presently disclosed technology takes advantage of the emission spectra of explosives (and other chemical compounds) on the clothes of a suspect.
  • a human being can be thought of as a 100 W light bulb in the infrared. Humans are blackbody radiators at 310 K. In sunlit scenes humans provide between 100 and 1000 times more IR radiance than the reflected sun in the 1 ⁇ m - 12 ⁇ m wavelength region.
  • the infrared image of a person (7 ⁇ m - 12 ⁇ m) shows emission from the person and their clothing.
  • the region of interest is the emission from the person's clothing.
  • Clothing is opaque in the 7 ⁇ m - 12 ⁇ m wavelength range, so the observed radiation will be from emission and reflection.
  • the source of reflected radiation (e.g., the sun during daylight hours) is ⁇ l/100th of the intensity of the radiation from the human, so the predominant radiation source is emission.
  • Clothing on a person will be at approximately 300 K depending on local temperature, layers, folds and wind. Contaminants on the clothing will be at approximately the same temperature but have a different emissivity. The change in emissivity will be characteristic of the infrared vibration and rotation resonance of the contaminant in the observed wavelength region (7 - 12 ⁇ m) .
  • the emissivity of any material at a particular wavelength is the same as the absorption of the material at the same wavelength.
  • a substance that has a particular absorption spectra in the IR will emit with exactly the same spectral characteristics.
  • a cooled Forward Looking Infrared (FLIR) Camera 10 designed to operate in the 7 - 12 ⁇ m wavelength range, such as illustrated in Fig. 2.
  • a camera typically includes a cooled detector array 12 within a cooled enclosure or container 14.
  • an imaging lens 16 and, as discussed below, preferable including a cooled band pass filter (s) 18 and a tunable Fabry-Perot Etalon or Interferometer 20.
  • the band pass filter (s) are in one example provided as filter wheels inside the cooled body of the camera.
  • band pass filters that select the resonance of any active functional group. If the materials of interest contain NO x , it is possible to select appropriate band pass filters. If the materials are aromatic, it is possible to select filters that pass the ring resonances. If the materials are peroxides, the appropriate band pass filters are available. To observe classes of compounds one band pass filter is sufficient, but to be more specific in terms of identification, more than one band pass filter will be utilized.
  • Fig. 2 shows a simulated scene with two people. One of the persons has a contaminant on her clothing. The image passes through a band pass filter in the FLIR as illustrated in Fig. 3 and the second image of the simulated scene is produced. Most of the contaminants shown in Fig. 2 are now absent. However, the contaminant images under the arm and on the sleeve remain. The implication is the contaminant emits at the NO x stretch wavelengths (6.4 - 6.7 ⁇ m, 7.3 - 7.8 ⁇ m) and therefore is observable .
  • Fig. 4 is a schematic of the etalon and spectra of two orders, the FSR and finesse. Finesse is a function of reflectivity; an etalon with high finesse shows sharper transmission peaks with lower minimum transmission coefficients.
  • the etalon will be scanned over the wavelength range of interest (-7.0 - 8.0 ⁇ m) in steps of for example 0.1 ⁇ m.
  • the image of the contaminant will be projected onto a set of pixels in the FLIR camera detector array 12 and the intensity versus wavelength spectra of the contaminant over the scanned range will be obtained.
  • the spectrum provides a more specific identification of the contaminant.
  • Thermal effects or gradients can be removed by subtracting, pixel-by-pixel, the Fabry-Perot etalon image at 7.1 ⁇ m from the image at 7.2 ⁇ m, the image at 7.2 ⁇ m from the image at 7.3 ⁇ m and so on (i.e., differential spectroscopy), leaving the changes due to emissivity. These effects are the resonances associated with the contaminants on the clothing, which is the signal of interest.
  • a Fabry-Perot etalon 20 can be used to supplement the band pass filters 18 described above, to select specific wavelength regions of the infrared spectra within the spectral range of the FLIR camera 10 (i.e., 7.0 - 12.0 ⁇ m) .
  • Band pass filters 18 can be used to help eliminate the issues associated with the multiple order overlap of the Fabry- Perot etalon.
  • Fig. 5 shows the simulated scene observed with a FLIR camera 10 and a Fabry-Perot etalon 20, the filter being used for order sorting.
  • the image passed through a Fabry-Perot etalon is focused through a band pass filter 18 and onto the camera detector array 12.
  • the etalon scans about 0.1 ⁇ m of the FSR from 7.2 - 8.5 ⁇ m.
  • the spectra associated with the emission from the contaminant is recorded and identified.
  • a band pass filter eliminates emission from other resonant wavelengths.
  • the presently disclosed Passive Infrared FLIR Image Spectroscopic Sensor identifies explosive (or other chemical) compounds on a person in the field of view at up to 50 m. It can be adapted to other explosives and other compounds, and finds applicability to other potential weapons-bearing threats such as vehicle, buildings and containers. By adapting the etalon for the particular application it is possible to identify a wide variety of chemical compounds, in this case explosives. It can be used at 50 m or more, a threshold that keeps the sensor system and operator safe during the measurements .
  • the initial infrared image will be gathered at -100 Hz or in 10 ms. Scanning the Fabry-Perot etalon 1.5 ⁇ m and acquiring fifteen images will take ⁇ 200 ms. If a band pass filter is needed to select the wavelength region of interest, it will take several seconds to move it into the field of view. Processing time will be required for the spectrum. In addition, the effect of thermal gradients will need to be eliminated from the image. This will be accomplished by subtracting each image from the subsequent etalon step, pixel by pixel. The difference image/spectra will reveal non-thermal changes in the images (i.e., emissivity changes with wavelength) .
  • the operator will see the images as they are produced by the camera and difference images in -200 ms.
  • the changes can be displayed as a fifteen frame/second movie in wavelength and time or as a plot of the change in wavelength versus time, as shown in Fig. 5. It is projected that the operator will be able to see the movie or plot in one second from the capture. If another wavelength region needs to be scanned, it will take several seconds to change the band pass filter, scan the new wavelength, process the data and present the result to the operator.
  • the concentration of the detected TCA is estimated to be 3000 ⁇ glcm 2 , and it is estimated that the detection limit for ⁇ FLIRISS is about 300 ⁇ g/c ⁇ f.
  • a fingerprint contains about 100 ⁇ g of material or about one-third the instrument's estimated detection limit .
  • the Planck Equation for spectral radiant excitance is given by: where h is Planck's Constant, c is the speed of light, 2 is the wavelength, ⁇ is the spectral emissivity, hv is the energy of a photon (v being the frequency), k is Boltzmann's Constant, and T is the temperature.
  • the spectral emissivity contains the spectral signatures of all the electronic and vibrational transitions of the emitting material, including characteristic vibrational frequencies that identify prominent chemical components of explosives (or other compounds of interest) .
  • M ⁇ is often expressed in Watts per square meter of area per micrometer of wavelength band.
  • the radiant excitance in band per micrometer from ⁇ i to ⁇ 2 is :
  • the resulting radiant excitance M(T) for both temperatures is shown in the "background" curves.
  • An expanded scale is shown in Fig. 7. Because the cited Gittins paper discusses radiance, that parameter is used here .
  • the spectral radiance and radiance respectively are given, assuming a Lambertian source, by:
  • the spectral radiance of a black body at 383 K is about 3500 ⁇ W/m 2 /sr/ ⁇ m, or about 40 times the reported contrast. Thus one expects a fractional change in contrast of one part in 40.
  • the maximum absolute value of a Lorentzian oscillator, expressed in terms of wavelength, near its peak is S ( ⁇ o/ ⁇ ) where ⁇ o is the resonance wavelength and ⁇ is the resonance linewidth (9.5 ⁇ and 0.5 ⁇ , respectively) .
  • FIG. 8 shows a detail of spectral radiance of the black body emission of a body at 383 K and at 300 K 1 both with an emissivity Lorentzian with a strength characteristic of TCA plumes observed in Gittins.
  • This curve is designated "target.”
  • the “difference” curve is obtained by subtracting these two and indicates the contrast to be expected. These curves are also shown in Figs. 6 and 7. Finally, on Fig. 8, the lowest curve is the noise-equivalent spectral radiance, NESR, 2 mw/cm 2 /sr/ ⁇ m.
  • noise-equivalent power (NEP) of a detector with a D-Star of: is computed as :
  • A is the area and B is the electrical bandwidth of the detection circuitry.
  • Square pixels, 40 ⁇ m on a side, and a bandwidth of 30 Hz are used, both from the cited Gittins article.
  • NEP NESRA ⁇ , where the solid angle is where NA is the numerical aperture of the camera lens, estimated at 1/2.4.
  • NA the numerical aperture of the camera lens
  • NEP 1.8 x 10 '12 W which is in excellent agreement with the value derived from the cited reference.
  • the spectra are converted to photon counts by multiplying the spectral radiance by A ⁇ to obtain power, then multiplying by 1/B to obtain energy, and finally dividing by the energy of a photon, hv, to obtain photon counts as functions of wavelength. Results are shown in Fig. 9. The choice of the 8 to 14 ⁇ m band is obviously a good one. The SNR exceeds 10 dB for this rather limited contrast.
  • PV NRT,- where P is pressure, V the volume, J? the gas constant, T the temperature, and N the number of gram moles of agent.
  • PVpv NRT, where pv is the volume density.
  • the mass per unit volume is m W 1n N m P
  • the detection limit is estimated to be about 100 ⁇ g/c ⁇ i 2 .
  • the waveform analysis, comparison, and reporting can be performed by any one of a number of conventional processors including specially programmed personal computers or custom configured circuits .
  • the ⁇ FLIRISS system can be utilized on its own or as part of an integrated sensor platform.
  • One example of such a platform includes five integrated sensors.
  • An intelligent video and data handling system identifies and tracks people in and entering in to a surveillance zone, starting at a distance of greater than 50 meters.
  • the video and data systems act as a first sensor to provide a ground-based coordinate system and motion-compensated tracking coordinates for the other sensors . It also alerts and provides tracking coordinates for each of the sensors when a person comes in range and marks the people with the results of the multi-sensor interrogation.
  • the ⁇ FLIRISS as discussed above, identifies explosives (or other chemical compounds) present on the person being tracked.
  • the ⁇ FLIRISS camera will examine the person. If there is reason to continue the surveillance, the Fabry-Perot Etalon will scan through the preselected wavelength range, for example 7.5 - 9.0 ⁇ m in 0.1 ⁇ m steps. The thermal gradients in the image will be eliminated by subtracting the image from one Etalon step to the next, pixel by pixel. The difference image/spectra will reveal non-thermal changes in the images (i.e., emissivity changes with wavelength) . The resulting difference spectrum will be analyzed and presented to the operator. The result of the surveillance will be recorded in a database and the person will be tagged (in the video image as well if part of the integrated platform) with the result.

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Abstract

A Passive Infrared FLIR Image Spectroscopic Sensor (πFLIRISS) system for detecting and identifying explosives at >50 m. Photons are continuously radiated from a person's clothing. Superimposed on the blackbody emission curves will be infrared spectral patterns due to clothing fabric, including any telltale spectral patterns of possible explosive traces. Most relevant explosive materials exhibit specific infrared spectra absorption and emission fingerprints which are detected and identified by the πFLIRISS system. An integrated, relatively long range threat detection system which utilizes the πFLIRISS system is also disclosed.

Description

TITLE OF THE INVENTION Passive Infrared FLIR Image Spectroscopic Sensor
CROSS REFERENCE TO RELATED APPLICATIONS
The present application claims priority of U.S. Provisional Patent Application No. 60/830,637, filed July 13, 2006, the entirety of which is incorporated herein by reference .
STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH OR
DEVELOPMENT n/a
BACKGROUND OF THE INVENTION
Body-worn explosive devices are a growing and important threat to both civilians and the military. Being small, these improvised explosive devices (IEDs) are hidden under the clothing of suicide bombers. Since they are often built out of non-standard parts, these explosives are hard to detect, especially at a safe distance. It is important to develop a sensor suite that can detect whether a person is wearing such an explosive device at sufficient distance to prevent him from entering populated or strategically important areas.
BRIEF SUMMARY OF THE INVENTION
Detecting and identifying explosive compounds (or other chemical) at a distance >50 m is the most challenging issue associated with suicide bomb detection. Applicants have developed a concept for a Passive Infrared FLIR Image Spectroscopic Sensor (πFLIRISS) that promises to detect and identify explosives (or other chemical compounds) at >50 m. When combined with a suite of sensors and an associated operating system, the opportunity to survey, detect, and react to a suicide bomber at distances greater than 50 m is substantial. It is estimated the detection limit for πFLIRISS is approximately 300 μg/cπ?. To provide some perspective, a single fingerprint left on a glass slide weighs about 100 μg, only a factor of three less than the instrument's estimated detection limit.
Trace amounts of explosive materials (or other chemical compounds) , found on the clothing a potential suicide bomber, can be detected by infrared (IR) emission spectral imaging at a distance of about 50 m. Many explosive are sticky, waxy compounds with low vapor pressure.1 They are easily transferred from the bulk explosives to hands, clothing, and equipment, and once they are transferred they stick around for a long time (i.e., months). The proposed detection scheme is based on the assumption that the inside of clothing material is in thermal equilibrium with the wearer's body (37 0C, or 310 K). The temperature differential between the body and the clothes' surface temperature is assumed to be about 9 0C. Thus, the clothing can be approximated as a 28 0C (301 K) blackbody. Assuming an average ambient temperature of 15 0C (288 K) , an enormous number of photons are continuously radiated from a person's clothing into the surroundings. Superimposed on the blackbody emission curves will be the infrared spectral patterns due to the fabric of the clothing, including any telltale spectral patterns of possible explosive traces.
The difficulty in carrying out the proposed detection of stains of explosive (or other chemical) compounds on a suicide bomber's clothing lies in the fact that there are numerous explosives, and that there are numerous clothing materials and dyes. However, most of the highly explosive materials used by suicide bombers are based on organic molecules incorporating specific molecular functional groups (nitro, acetal, peroxyl, ... groups) with the general formula R-(NO2Jx, R-C=O, R-O=O. These molecules exhibit specific fingerprints in the infrared absorption and infrared emission spectra, which can be used for their identification. In order to discriminate the spectral features of explosive materials from the spectra of the background (which will contain the signatures of the clothing material and dyes used in their production) , hyperspectral data acquisition and manipulation are utilized.
An integrated system which utilizes the πFLIRISS system is also disclosed. A combination of four sensor technologies with the πFLIRISS for explosives detection enables the ability to survey, detect, and react to a suicide bomber at distances greater than 50 m. The presently disclosed concepts are also applicable to suspect vehicles, buildings, and containers.
BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWINGS
The invention will be more fully understood by reference to the following description in conjunction with the accompanying drawings, of which:
Fig. 1 is a table illustrating properties of various explosives;
Fig. 2 illustrates an infrared camera and associated elements according to the presently disclosed invention, along with an exemplary image achieved therewith;
Fig. 3 illustrates an exemplary bandpass filter curve which can be incorporated into the infrared camera of Fig. 2, along with an exemplary image achieved therewith;
Fig. 4 illustrates the basic structure and response of a Fabry-Perot Etalon which can be incorporated into the infrared camera of Fig. 2;
Fig. 5 illustrates a detected transmission resulting from use of the infrared camera of Fig. 2 in conjunction with the bandpass filter of Fig. 3 and the Fabry-Perot Etalon of Fig. 4 and exemplary images achieved therewith;
Fig. 6 is a graph of radiant excitance through a 100 nanometer bandpass filter; Fig. 7 is a graph of the radiant excitance through a 100 nanometer bandpass filter of Fig. 6 in an expanded view;
Fig. 8 is a graph of spectral radiance plots for the data of Fig. 7;
Fig. 9 is a graph of photon counts of the spectra of Fig. 6; and
Fig. 10 is a graph of the calculated derivative emissivity signal from the source in Fig. 6.
DETAILED DESCRIPTION OF THE INVENTION
Explosives are sticky, waxy compounds with low vapor pressure. Residue is easily transferred from the bulk explosives to hands, clothing, and equipment, and once transferred to a person's clothing, it remains for a long time (e.g., weeks and months) .
A human is a blackbody radiator at about 310 K. In the 1 μm - 12 μm wavelength spectrum, the intensity of infrared radiation emitted by a human is about 100 times more intense than the reflected ambient light from the sun. Clothing on a human is also at about 300 K and is a radiator, as is any contaminant (e.g., explosives or other chemical compounds) on the clothing.
Explosives are chemical compounds that have specific absorption and emission spectra in the infrared. The functional groups in explosives (or other chemical compounds) resonate (i.e., absorb and emit) at specific infrared wavelengths.
Forward Looking InfraRed (FLIR) cameras detect infrared radiation in the 7 μm - 12 μm wavelength range. By tuning a FLIR camera (using, for example, band pass filters for sorting and a Fabry-Perot etalon for spectral scanning) to see specific functional group resonances in the emission spectra, it is possible to detect explosive contaminants or other chemical compounds on clothing, in the camera's image, at a significant distance. Spectral hypercubes consist of X and Y coordinates of pixels from a detector array 12, and λ coordinate in which spectral data are collected. The result is a complete or partial spectrum associated with the image projected on each pixel. For the imaging of a person's clothing, a system is utilized to image an area of about 30 x 30 cm2 (representative of a person's upper torso) via appropriate infrared optics onto a 128 x 128 element focal plane array (FPA) . Each of the detector elements measures approximately 30 μm on edge in one embodiment, for a total array size of about 3.8 x 3.8 /ran2. Prior to detection by the FPA, the IR radiation emitted from the target is analyzed by a band-pass filter 18 to prevent order overlap and a tunable etalon filter 20 with a band pass of about 2 cm"1 in the 3100 to 2800 and the 1400 to 900 cm'1 spectral regions. The resulting hypercube will contain between 300 and 500 intensity values for each of the 128 x 128 (=16384) pixels . Convoluted into each pixel in the snap shot in the cube is a part of the image projected onto the pixel, λ selected by the filter and the etalon and time corresponding to the event time.
The stains and smudges from explosives (and other chemical compounds) exhibit infrared spectral patterns, which are distinctly different from those of the surrounding materials, and can be identified via multivariate methods of analysis. Many explosives (e.g., RDX, DEGN, PETN, TNT) contain nitrate groups, others (e.g., HMX, MEDINA, EDNA) contain amine groups, while still others contain peroxides, ketones (e.g., TATP), or acids (e.g., Picric acid) . Nitrates resonate at ~ 6, 8 and 11 μm; amines resonate at ~ 3, 6, and 11 μm; peroxides resonate at ~ 12 μm; ketones at about ~ 6 μm; and acids resonate about ~ 6, 7, 8, and 10 μm. By changing the band pass filter 18 and scanning the Fabry- Perot Etalon 20, the different IR spectral regions can be examined. Many of these characteristic IR vibrational lines lie in the 3 - 5 μm and 8 - 14 μm bands of relative atmospheric transparency and are suitable for detection at stand-off ranges on the order of 50 in.
Explosives have two physical properties of particular interest. As a class of compounds, they behave like long chain (e.g., C16 n-alkanes) waxes. In addition, and with reference to Fig. 1, they have low vapor pressure and are sticky. These properties are useful if one is looking for the compounds on the surface of clothing. People handling the compounds easily get them on their hands and clothing and the contamination stays on their clothing for weeks or months .
As discussed, all explosive materials (and other chemical compounds) are active in infrared wavelengths (i.e., 2 - 15 μm) and have unique, individual spectra. Many of the compounds contain NOx. Some are ring compounds (i.e., aromatic), while others are peroxides. All of them have identifiable spectra in the 7 - 12 μm wavelength range and can be identified by their unique spectra.
- NOx (stretch) (6.4 - 6.7 μm, 7.3 - 7.8 μm)
- Ring (stretch, wobble) (3.1 - 3.6 μm)
- CO (stretch) (8.3 μm)
When identifying compounds, it is preferable to identify multiple resonances or functional groups to improve specificity.
Most frequently, infrared spectra are observed by transmitting infrared emission through a sample of a solid mixture, solid or gas. However, resonance of a molecular vibration or rotation spectra with infrared electromagnetic radiation can also be measured from reflected or emitted radiation. The presently disclosed technology takes advantage of the emission spectra of explosives (and other chemical compounds) on the clothes of a suspect.
A human being can be thought of as a 100 W light bulb in the infrared. Humans are blackbody radiators at 310 K. In sunlit scenes humans provide between 100 and 1000 times more IR radiance than the reflected sun in the 1 μm - 12 μm wavelength region.
Spectral Radiance {W/m2 * steradian)
Ukmi) Human Sun
2. 0 1.50 E-02 1.08 E-Ol
4. 0 5.22 E+01 9.51 E-03
7. 0 4.63 E+02 1.16 E-03
11 .0 5.48 E+02 2.04 E-04
Some of this radiation is insulated by multiple layers of clothing. Some is carried away by the atmosphere (convection, conduction and radiation) . The net result is lower flux emitted by our clothing than by our skin, as can be seen in the infrared image of a person in Figure 2. The infrared image of a person (7 μm - 12 μm) shows emission from the person and their clothing. In the present context, the region of interest is the emission from the person's clothing. Clothing is opaque in the 7 μm - 12 μm wavelength range, so the observed radiation will be from emission and reflection. The source of reflected radiation (e.g., the sun during daylight hours) is ~l/100th of the intensity of the radiation from the human, so the predominant radiation source is emission.
Clothing on a person will be at approximately 300 K depending on local temperature, layers, folds and wind. Contaminants on the clothing will be at approximately the same temperature but have a different emissivity. The change in emissivity will be characteristic of the infrared vibration and rotation resonance of the contaminant in the observed wavelength region (7 - 12 μm) .
By the thermodynamic principle of detailed balance, the emissivity of any material at a particular wavelength is the same as the absorption of the material at the same wavelength. A substance that has a particular absorption spectra in the IR will emit with exactly the same spectral characteristics.
It is possible to observe the radiation in the wavelength region of interest using a cooled Forward Looking Infrared (FLIR) Camera 10 designed to operate in the 7 - 12 μm wavelength range, such as illustrated in Fig. 2. Such a camera typically includes a cooled detector array 12 within a cooled enclosure or container 14. Also provided is an imaging lens 16 and, as discussed below, preferable including a cooled band pass filter (s) 18 and a tunable Fabry-Perot Etalon or Interferometer 20. The band pass filter (s) are in one example provided as filter wheels inside the cooled body of the camera. By choosing the camera and filter appropriately, it is possible to look at a spectral range (~8 μm) where NOx is resonant.
The strength of this approach is that it is possible to choose band pass filters that select the resonance of any active functional group. If the materials of interest contain NOx, it is possible to select appropriate band pass filters. If the materials are aromatic, it is possible to select filters that pass the ring resonances. If the materials are peroxides, the appropriate band pass filters are available. To observe classes of compounds one band pass filter is sufficient, but to be more specific in terms of identification, more than one band pass filter will be utilized.
By selecting the wavelength region between 7 - 8 μm, it is possible to determine if the contaminant on a person in the field of camera view emits at these wavelengths . The image of the contaminant will appear in the image if it emits and it will disappear if it does not. Fig. 2 shows a simulated scene with two people. One of the persons has a contaminant on her clothing. The image passes through a band pass filter in the FLIR as illustrated in Fig. 3 and the second image of the simulated scene is produced. Most of the contaminants shown in Fig. 2 are now absent. However, the contaminant images under the arm and on the sleeve remain. The implication is the contaminant emits at the NOx stretch wavelengths (6.4 - 6.7 μm, 7.3 - 7.8 μm) and therefore is observable .
Many compounds emit radiation in the wavelength range of the band pass filter (7.0 - 8.0 μm) . To obtain more specific identification, an intensity versus wavelength spectrum can be obtained to fingerprint the contaminant. The spectrum of the contaminant can be obtained from the FLIR camera with a Fabry- Perot etalon filter 20, as shown in Fig. 2. The etalon is a scanning interferometer matched to the application. It has an appropriate scan drive, Free Spectral Range (FSR) , and finesse for the application, so that an intensity versus wavelength spectrum can be obtained. There are commercially available Fabry-Perot etalons that provide the appropriate figures of merit for this application. Fig. 4 is a schematic of the etalon and spectra of two orders, the FSR and finesse. Finesse is a function of reflectivity; an etalon with high finesse shows sharper transmission peaks with lower minimum transmission coefficients.
The etalon will be scanned over the wavelength range of interest (-7.0 - 8.0 μm) in steps of for example 0.1 μm. The image of the contaminant will be projected onto a set of pixels in the FLIR camera detector array 12 and the intensity versus wavelength spectra of the contaminant over the scanned range will be obtained. The spectrum provides a more specific identification of the contaminant.
Thermal effects or gradients can be removed by subtracting, pixel-by-pixel, the Fabry-Perot etalon image at 7.1 μm from the image at 7.2 μm, the image at 7.2 μm from the image at 7.3 μm and so on (i.e., differential spectroscopy), leaving the changes due to emissivity. These effects are the resonances associated with the contaminants on the clothing, which is the signal of interest. A Fabry-Perot etalon 20 can be used to supplement the band pass filters 18 described above, to select specific wavelength regions of the infrared spectra within the spectral range of the FLIR camera 10 (i.e., 7.0 - 12.0 μm) .
Band pass filters 18 can be used to help eliminate the issues associated with the multiple order overlap of the Fabry- Perot etalon. Fig. 5 shows the simulated scene observed with a FLIR camera 10 and a Fabry-Perot etalon 20, the filter being used for order sorting. In this embodiment, the image passed through a Fabry-Perot etalon is focused through a band pass filter 18 and onto the camera detector array 12. The etalon scans about 0.1 μm of the FSR from 7.2 - 8.5 μm. The spectra associated with the emission from the contaminant is recorded and identified. A band pass filter eliminates emission from other resonant wavelengths.
The presently disclosed Passive Infrared FLIR Image Spectroscopic Sensor (πFLIRISS) identifies explosive (or other chemical) compounds on a person in the field of view at up to 50 m. It can be adapted to other explosives and other compounds, and finds applicability to other potential weapons-bearing threats such as vehicle, buildings and containers. By adapting the etalon for the particular application it is possible to identify a wide variety of chemical compounds, in this case explosives. It can be used at 50 m or more, a threshold that keeps the sensor system and operator safe during the measurements .
The initial infrared image will be gathered at -100 Hz or in 10 ms. Scanning the Fabry-Perot etalon 1.5 μm and acquiring fifteen images will take ~200 ms. If a band pass filter is needed to select the wavelength region of interest, it will take several seconds to move it into the field of view. Processing time will be required for the spectrum. In addition, the effect of thermal gradients will need to be eliminated from the image. This will be accomplished by subtracting each image from the subsequent etalon step, pixel by pixel. The difference image/spectra will reveal non-thermal changes in the images (i.e., emissivity changes with wavelength) . The operator will see the images as they are produced by the camera and difference images in -200 ms. The changes can be displayed as a fifteen frame/second movie in wavelength and time or as a plot of the change in wavelength versus time, as shown in Fig. 5. It is projected that the operator will be able to see the movie or plot in one second from the capture. If another wavelength region needs to be scanned, it will take several seconds to change the band pass filter, scan the new wavelength, process the data and present the result to the operator.
In this section, it is shown that sufficient sensitivity is expected to detect infrared signatures from traces of explosive (or other chemical compounds) on clothing. We extrapolate this result from data reported on gaseous 1, 1, 1-trichloroethane (TCA) at a concentration of 1000 ppmv in a plume in the atmosphere, as reported in Gittins et al., "Remote Characterization of Chemical Vapor Plumes by LWIR Imaging Fabry-Perot Spectrometry, " Fifth Joint Conference on Standoff Detection for Chemical and Biological Defense, CB Standoff: An integrated Future, Sept., 2001 (hereinafter "Gittins"). In Figure 7 of that presentation, the authors show a spectral radiance contrast of 80 μw/cπf/sr/μm on a hot plume of TCA from a chimney having a diameter of 0.5 m. The emissivity contrast required to produce this result is computed, and then the spectral signatures of clothing at 300 K are computed, resulting in the same emissivity contrast. The noise- equivalent spectral radiance (NESR) reported in Gittins is consistent with that estimated from typical detector D-Star values. The target spectra is converted to photon counts, and the signal and noise are analyzed, using both quantum noise and the reported NESR. Finally, the concentration of the agent on clothing which produces the same contrast as the atmospheric plume is estimated. It is shown that: - The contrast is well above the noise with a 100 nm line width;
- The quantum noise is well below the noise associated with the NESR; and
- The concentration of the detected TCA is estimated to be 3000 μglcm2, and it is estimated that the detection limit for πFLIRISS is about 300 μg/cπf.
To provide some comparison, a fingerprint contains about 100 μg of material or about one-third the instrument's estimated detection limit .
The Planck Equation for spectral radiant excitance is given by:
Figure imgf000014_0001
where h is Planck's Constant, c is the speed of light, 2 is the wavelength, ε is the spectral emissivity, hv is the energy of a photon (v being the frequency), k is Boltzmann's Constant, and T is the temperature. The spectral emissivity contains the spectral signatures of all the electronic and vibrational transitions of the emitting material, including characteristic vibrational frequencies that identify prominent chemical components of explosives (or other compounds of interest) .
Mχ is often expressed in Watts per square meter of area per micrometer of wavelength band. The radiant excitance in band per micrometer from λi to λ2 is :
M(T)=^Mλ(T,λ)dλ
The radiant excitance is shown in Fig. 6 at a temperature of 300 K1 and at the higher temperature of 383 K (110° C) . It is assumed that the emissivity of clothing is about ε= 0.9. The resulting radiant excitance M(T) for both temperatures is shown in the "background" curves. An expanded scale is shown in Fig. 7. Because the cited Gittins paper discusses radiance, that parameter is used here . The spectral radiance and radiance respectively are given, assuming a Lambertian source, by:
Lx(T,X)=Mx(T,X)Iπ and
L(T)=M(T)Iπ
The spectral radiance of a black body at 383 K is about 3500 μW/m2/sr/μm, or about 40 times the reported contrast. Thus one expects a fractional change in contrast of one part in 40. The maximum absolute value of a Lorentzian oscillator, expressed in terms of wavelength, near its peak is S (λo/Δλ) where λo is the resonance wavelength and Δλ is the resonance linewidth (9.5 μ and 0.5 μ, respectively) .
A 1/40 emission peak yields a dimensionless oscillator strength S of 1.3 x 10"3. Fig. 8 shows a detail of spectral radiance of the black body emission of a body at 383 K and at 300 K1 both with an emissivity Lorentzian with a strength characteristic of TCA plumes observed in Gittins.
This curve is designated "target." The "difference" curve is obtained by subtracting these two and indicates the contrast to be expected. These curves are also shown in Figs. 6 and 7. Finally, on Fig. 8, the lowest curve is the noise-equivalent spectral radiance, NESR, 2 mw/cm2/sr/μm.
The noise-equivalent power (NEP) of a detector with a D-Star of:
Figure imgf000015_0001
is computed as :
NEP = ÷ά£- = 2.2x10~12 Watts ,
where A is the area and B is the electrical bandwidth of the detection circuitry. Square pixels, 40 μm on a side, and a bandwidth of 30 Hz are used, both from the cited Gittins article. Starting with the specified NESR,
NEP=NESRAΩΔλ , where the solid angle is where NA is the numerical aperture of the camera lens, estimated at 1/2.4. For NESR = 2 μW/ςm2/sr/μm, one obtains
NEP = 1.8 x 10'12 W which is in excellent agreement with the value derived from the cited reference.
The spectra are converted to photon counts by multiplying the spectral radiance by AΩΔλ to obtain power, then multiplying by 1/B to obtain energy, and finally dividing by the energy of a photon, hv, to obtain photon counts as functions of wavelength. Results are shown in Fig. 9. The choice of the 8 to 14 μm band is obviously a good one. The SNR exceeds 10 dB for this rather limited contrast.
One can relate the atmospheric concentration of TCA in the cited experiments to concentration of an agent on clothing. First, the density (mass per unit volume) of agent in the air is computed from the volume density. Using the gas law,
PV = NRT,- where P is pressure, V the volume, J? the gas constant, T the temperature, and N the number of gram moles of agent. For the species of interest,
PVpv = NRT, where pv is the volume density. The mass per unit volume is m W1nN m P
V V " RT where Wn, is the molecular weight. Assuming the weight of one gram mole is Wm = 132 g, and J? = 8.31 J/mol/K, and using T = 383 K for the hot plume, P = 97 kN/m2, and a column length estimated at €c = 2m, = WJcpv — « — y . Note : 1 mg/crr?
Area RT cm
This last calculation assumes that the emission from molecules in a condensed film is equivalent to the emission of the same number of molecules in a gas. Nevertheless, it is a good first estimate of the detectable material density. Based on an experimental signal-to-noise ratio of ten, the detection limit is estimated to be about 100 μg/cπi2.
The waveform analysis, comparison, and reporting can be performed by any one of a number of conventional processors including specially programmed personal computers or custom configured circuits .
The πFLIRISS system can be utilized on its own or as part of an integrated sensor platform. One example of such a platform includes five integrated sensors. An intelligent video and data handling system identifies and tracks people in and entering in to a surveillance zone, starting at a distance of greater than 50 meters. The video and data systems act as a first sensor to provide a ground-based coordinate system and motion-compensated tracking coordinates for the other sensors . It also alerts and provides tracking coordinates for each of the sensors when a person comes in range and marks the people with the results of the multi-sensor interrogation.
The πFLIRISS, as discussed above, identifies explosives (or other chemical compounds) present on the person being tracked.
The πFLIRISS camera will examine the person. If there is reason to continue the surveillance, the Fabry-Perot Etalon will scan through the preselected wavelength range, for example 7.5 - 9.0 μm in 0.1 μm steps. The thermal gradients in the image will be eliminated by subtracting the image from one Etalon step to the next, pixel by pixel. The difference image/spectra will reveal non-thermal changes in the images (i.e., emissivity changes with wavelength) . The resulting difference spectrum will be analyzed and presented to the operator. The result of the surveillance will be recorded in a database and the person will be tagged (in the video image as well if part of the integrated platform) with the result.
Fig. 10 shows the dielectric susceptibility, normal incidence reflection, and derivative emissivity (= derivative absorption = -derivative reflection) of a Lorentzian oscillator with an oscillator strength of 1 x 10"4, smaller than the oscillator strength of the TCA plume measured in Gittins. Cataloging the spectra peaks and dips in the dE/dv spectrum and comparing with signatures of explosives (or other compounds) will result in remote identification of threats or other targets of interest.
While the present invention has been described in conjunction with a preferred embodiment, one of ordinary skill, after reading the foregoing specification, will be able to effect various changes, substitutions or equivalents, and other alterations to the compositions and methods set forth herein. It is therefore intended that the protection granted by Letters Patent hereon be limited only by the definitions contained in the appended claims and equivalents thereof .

Claims

CLAIMS What is claimed is :
1. A method of analyzing a remote surface for the presence of explosive chemical compounds, comprising: focusing a forward looking infrared detector on a portion the remote surface,- restricting the wavelengths of the detected infrared emissions to a range of interest; measuring the intensity of emission at each of successive wavelengths within the range of interest; assembling an intensity of emission versus wavelength spectrum for the range of interest from the measurements at the successive wavelengths; comparing the assembled intensity versus wavelength spectrum to at least one predetermined spectrum associated with a respective explosive chemical compound; and identifying the presence of an explosive chemical compound on the portion of the remote surface if a correlation results from the step of comparing the assembled intensity versus wavelength spectrum against the at least one respective predetermined spectra.
2. The method of claim 1, further comprising the step of compensating for thermal effects in the assembled intensity versus wavelength spectrum.
3. The method of claim 2, wherein the step of compensating comprises the step of subtracting the measured intensity of emission at one wavelength within the range of interest from the measured intensity of emission at the next, successive wavelength within the range of interest.
4. The method of claim 1, wherein the steps of measuring and obtaining are performed using a scanning interferometer.
5. The method of claim 4, wherein the steps of measuring and obtaining are performed using a Fabry-Perot etalon.
6. The method of claim 1, wherein the step of restricting is performed using a bandpass filter.
7. A system for analyzing a remote surface to detect the presence of explosive chemical compounds thereon, comprising: a forward looking infrared detector for focusing on a portion of the remote surface and for detecting infrared emissions therefrom; a bandpass filter for restricting the wavelengths of the detected infrared emissions to a range of interest; a scanning spectrometer for enabling the detector to measure the intensity of emission at each of successive wavelengths within the range of interest; a database of predetermined spectra associated with respective explosive chemical compounds; and a processor for assembling discrete intensity measurements into a measured spectrum, for comparing the measured spectrum to the predetermined spectra in the database, and, if a match is established, identifying the explosive chemical compound associated with the matched predetermined spectrum as being present on the remote surface.
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US9052290B2 (en) 2012-10-15 2015-06-09 Chemimage Corporation SWIR targeted agile raman system for detection of unknown materials using dual polarization
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US8994934B1 (en) 2010-11-10 2015-03-31 Chemimage Corporation System and method for eye safe detection of unknown targets
US9052290B2 (en) 2012-10-15 2015-06-09 Chemimage Corporation SWIR targeted agile raman system for detection of unknown materials using dual polarization
EP3692347A4 (en) * 2017-10-06 2021-09-22 Bio-Rad Laboratories, Inc. Protein quantitation device
US11435285B2 (en) 2017-10-06 2022-09-06 Bio-Rad Laboratories, Inc. Protein quantitation device
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