Comparison of the Inversion Periods 

for Mid-wave IR (MidIR) and Long-wave IR (LWIR) 

Polarimetric and Conventional Thermal Imagery 

by M. Felton, K. P. Gurton, J. L. Pezzaniti, D. B. Chenault, and L. E. Roth 

ARL-TR-5153 April 2010 

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Army Research Laboratory 

Adelphi, MD 20783-1197 

ARL-TR-5153 April 2010 

Comparison of the Inversion Periods 

for Mid-wave IR (MidIR) and Long-wave IR (LWIR) 

Polarimetric and Conventional Thermal Imagery 

M. Felton and K. P. Gurton 

Computational and Information Sciences Directorate, ARL 

J. L. Pezzanitib and D. B. Chenault 

Polaris Sensor Technologies, Inc. 

200 Westside Square, Suite 320, Huntsville, AL, 35801 

L. E. Roth 

U.S. Army Armament Research and Development Engineering Center 

Picatinny Arsenal, NJ, USA 07806-5000 

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Comparison of the Inversion Periods for Mid-wave IR (MidIR) and Long-wave 

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14. ABSTRACT 

We report the results of a diurnal study that recorded radiometrically calibrated polarimetric and conventional thermal 

imagery in the mid-wave IR (MidIR) and long-wave IR (LWIR) to identify and compare the respective time periods in which 

minimum target contrast is achieved. The MidIR polarimetric sensor is based on a division-of-aperture approach and has a 

640×512 indium antimonide (InSb) focal-plane array (FPA), while the LWIR polarimetric sensor uses a spinning achromatic 

retarder to perform polarimetric filtering and has a 324 x 256 microbolometer FPA. The images used in this study include the 

S0 and S1 Stokes images of a scene containing a military vehicle and the natural background. Relevant meteorological 

parameters measured during the test period include air temperature, ambient loading in the LWIR, relative humidity, cloud 

cover, height, and density. The data show that the chief factors affecting polarimetric contrast in both wavebands are the 

amount of thermal emission from the objects in the scene and the abundance of MidIR and LWIR sources in the optical 

background. In particular, we observed that the MidIR polarimetric contrast was positively correlated to the presence of 

MidIR sources in the optical background, while the LWIR polarimetric contrast was negatively correlated to the presence of 

LWIR sources in the optical background. 

15. SUBJECT TERMS

Polarimetric imaging, thermal imaging, microbolometer, target contrast, inversion periods 

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iii 

Contents 

List of Figures iv

List of Tables iv

Acknowledgments v

1. Introduction 1

1.1 Thermal Polarimetric Imaging ........................................................................................1

2. Experiment 2

2.1 MidIR Polarimetric Sensor ..............................................................................................2

2.2 LWIR Polarimetric Sensor ..............................................................................................3

2.3 Field Test Site ..................................................................................................................4

2.4 Image Analysis ................................................................................................................6

3. Results 8

3.1 Diurnal Standardized S0 and S1 .......................................................................................8

3.2 Diurnal Contrast ............................................................................................................10

4. Conclusions 12

5. References 14

List of Symbols, Abbreviations, and Acronyms 15

Distribution List 16 
iv 

List of Figures 

Figure 1. Schematic of the U.S. Army Research Laboratory (ARL) MidIR DOA imaging 

polarimeter. ................................................................................................................................3

Figure 2. ARL MidIR imaging polarimeter with DOA optics. .......................................................3

Figure 3. (Left) Picture of polarimetric sensor, and optical layout of the spinning retarder, 

microbolometer-based sensor, and (right) standard and polarimetric LWIR images. Note 

how background clutter in standard LWIR image is rejected in polarimetric image, 

revealing targets difficult to see in LWIR image. ......................................................................4

Figure 4. Precision Armaments Laboratory tower with elevator that housed the polarimetric 

sensor situated on the sixth floor. ..............................................................................................5

Figure 5. Target site consisting of two military vehicles and a natural background. The test 

was conducted on May 13, 2009, but this image was taken in the preceding fall. 

Therefore, during the test, the grass was alive and thick, and the bushes and trees 

contained leaves. ........................................................................................................................6

Figure 6. The test target and its natural background. The target, grass and trees regions of 

interest correspond to the blue, red and green boxes, respectively. .........................................7

Figure 7. Example contrast values comparing the target to the grass and the corresponding 

S0 image taken at a. 07:00, b. 11:00, and c. 19:00. ....................................................................8

Figure 8. Diurnal plots of standardized S0 values in the MidIR and LWIR for surrogate tank 

(blue), grass (red), and trees (green) regions of interest. ...........................................................9

Figure 9. Diurnal plots of standardized S1 values in the MidIR and LWIR for surrogate tank 

(blue), grass (red), and trees (green) regions of interest. .........................................................10

Figure 10. Diurnal contrast between the tank and its background of grass on May 13, 2009. .....11

Figure 11. Diurnal contrast between the tank and its background of trees on May 13, 2009. .....12

List of Tables 

Table 1. A summary of the MidIR sensor optical specs. ................................................................3

Table 2. Specifications for the LWIR imaging polarimeter. ..........................................................4

 
v 

Acknowledgments 

This work was accomplished using data from the Hyperspectral and Polarimetric Target 

Detection Program at the Precision Armament Laboratory (PAL) Tower at the Armament 

Research and Development Engineering Center (ARDEC) with the help of Mr. Joao Romano 

(Program Manager), Mr. Mark Woolley (PAL Manager), and Zed Habte (test engineer). 

 
vi 

INTENTIONALLY LEFT BLANK. 
1 

1. Introduction 

Thermal imagers have been established as the primary tool used in military and security 

activities that involve surveillance, targeting and tracking, and night-time operations. Unlike 

image intensification (I2

) devices, which depend on ambient light levels, thermal imagers exploit 

the fact that all objects with a temperature above 0 K emit thermal radiation by creating a 

pseudo-image of the scene based on this thermal emission. The two thermal imaging windows 

are the mid-wave IR (MidIR), 3–5 μm, and the long-wave IR (LWIR), 8–14 μm, both chosen for 

the relatively low amounts of absorption from atmospheric species, such as carbon dioxide (CO2) 

and water (H2O). 

Contrast between the objects within a thermal image is determined by their effective 

temperatures, which are a function of their true temperature and emissivity, a characteristic that 

describes how efficiently an object radiates absorbed energy as compared to a blackbody. If 

there is no thermal contrast between a target and its background, it cannot be seen in a thermal 

image. The diurnal cycles of the thermal properties of both manmade and natural objects tend to 

bring about periods of low contrast within thermal images, often referred to as thermal 

crossovers or inversion periods (1). These inversion periods tend to occur during periods of 

rapidly changing temperatures, such as sunrise and sunset, but may occur at any time throughout 

the day, depending both on temperature differences between objects and their backgrounds, and 

on environmental factors, such as solar loading. Thermal polarimetric imaging is a technology 

that enhances conventional thermal imaging by extending its operational ability into these 

periods of thermal inversion. 

1.1 Thermal Polarimetric Imaging 

Thermal polarimetric imaging has been proposed as a method to enhance conventional thermal 

imaging (2). It creates images of a scene that are based on the states of polarization of the IR 

light emitted or reflected from the objects within the scene. An object’s polarimetric signature is 

a function of its surface geometry and roughness. Due to the different geometrical and 

roughness features of objects constituting natural backgrounds and manmade objects, the 

polarization states of the emitted and reflected thermal light can be used as a discriminator 

between objects of interest and background clutter. Using the polarization of the light, it is 

possible to obtain an image of a scene that has polarimetric contrast between objects and their 

backgrounds even when there is no thermal contrast. 

In addition to the environmental factors that affect thermal contrast, there are also environmental 

factors that affect polarimetric contrast. The most significant of these factors involves sources of 

IR radiation in what has been referred to as the optical background. The optical background is 

defined as the IR radiation emitted by sources that are not necessarily visible within the scene, 
2 

but that still reflects off of an object and into the field of view (FOV) of the camera (3). 

Potential sources include vehicles, buildings, trees, clouds, water vapor, etc. The optical 

background can become partially polarized upon reflection and act as a competing component to 

the emitted polarized light. Polarized emitted and reflected light are often orthogonal to each 

other, because the emitted polarized light tends to be in the direction parallel to the surface 

normal, while light polarized upon reflection tends to be perpendicular to the surface normal. 

When the two components superpose, the effect can be a reduction in the magnitude of the 

polarimetric signature of an object. 

This study compares the temporal occurrence of conventional thermal inversion periods to 

polarimetric inversion periods and correlates these inversions with environmental factors. Our 

goals are to quantify the periods of time in which contrast within polarimetric images is present 

while conventional thermal contrast has been lost and to verify the impact of environmental 

factors such as clouds. Under these conditions, it can be concluded that polarimetric imaging is 

capable of enhancing conventional thermal imaging. 

2. Experiment 

2.1 MidIR Polarimetric Sensor 

A schematic of a division-of-aperture (DOA) MidIR imaging polarimeter architecture is 

illustrated in figure 1. A picture of the actual system is shown in figure 2. The system is based 

on a DOA lens technology developed by Polaris Sensor Technologies (4). The first element of 

the lens system (in figure 1) is a standard MidIR objective lens, which forms an image of the 

target on a field stop. The second set of optics shown inside the cryogenic chamber is the DOA 

optics. The collimation optic collimates the image from the field stop and forms an image of the 

objective lens aperture onto a 2×2 array of mini-lenses. The mini-lenses are in quasi-collimated 

space. The mini-lens set forms four identical images of the field stop onto four quadrants of the 

sensor focal plane array (FPA). When the DOA system operates as an imaging polarimeter, each 

mini-lens is followed by a linear polarizer at a different orientation. The DOA system can also 

be operated as a multi-spectral imager if each mini-lens is followed by a bandpass filter. For this 

system, a set of four linear wire-grid polarizers is used, oriented at angles 0°, 90°, 45°, and 135°. 

Thus, the FPA captures four images simultaneously of the object at these four different 

polarization states. The four images are precisely registered to within 1/10 pixel in software, and 

weighted subtractions are done to compute the Stokes images of the scene. The actual DOA lens 

set is much more complex than the schematic shown here and involves nine elements, but this 

illustrates the concept. Note that the image shown in figure 1 is an actual image taken with the 

system from the air of the Saturn V rocket located at the Space and Rocket Center, Huntsville, 

AL. The DOA output image shown to the right in figure 1 is actual output from the DOA lens 

set. Table 1 gives the optical specifications for the DOA MidIR imaging polarimeter. 
3 

Figure 1. Schematic of the U.S. Army Research Laboratory (ARL) MidIR DOA imaging polarimeter. 

Figure 2. ARL MidIR imaging polarimeter with DOA optics. 

Table 1. A summary of the MidIR sensor optical specs.

Parameter Value 

FOV 5.5° 

Objective focal length 100 mm 

f/# 2.3 

Total FPA pixels 640×512 

Pixel size 24×24 μm 

Quadrant aperture usable pixels 220×220 

Max frame rate (stream to disk) 87 fps (640×512) 

Sensor dimensions (mm) 420L×90W×210H 

Sensor weight 11 lb 

System noise equivalent radiance (NER) 1e-7 W/cm2-sr 

2.2 LWIR Polarimetric Sensor 

The LWIR imaging polarimeter is a microbolometer-based rotating retarder imaging polarimeter 

developed by Polaris Sensor Technologies, Inc., Huntsville, AL (figure 3) (5). It operates by 

capturing up to 12 images sequentially in time, each at a different orientation of the rotating 

retarder. Together, the retarder and linear polarizer act as a polarization state analyzer for the 

Objective Lens

Collimation 

Optic Aperture 

Division MiniLens Array

Field Stop & 

Intermediate 

Image Plane

Cryogenic 

temperature

FPA

Dewar
4 

light forming the image. Using the data reduction matrix method, the Stokes vectors are 

calculated, which completely characterizes the polarization states of the light from the scene. 

Table 2 lists the sensor specifications. 

Figure 3. (Left) Picture of polarimetric sensor, and optical layout of the spinning retarder, microbolometer-based 

sensor, and (right) standard and polarimetric LWIR images. Note how background clutter in standard 

LWIR image is rejected in polarimetric image, revealing targets difficult to see in LWIR image.

Table 2. Specifications for the LWIR imaging polarimeter. 

Parameter Value 

FOV 13.7°×11.0° 

Objective focal length 50 mm 

f/# 0.87 

Total FPA pixels 324×256 

Pixel size 38×38 m 

Max frame rate (stream to disk) 30 fps 

Sensor dimensions (mm) 10L × 6W × 7.5H 

Sensor weight 12 lb 

Power 15 V, 1.2 A 

2.3 Field Test Site 

The test was conducted at the Precision Armaments Laboratory located in Picatinny Arsenal, NJ. 

The camera was situated on the sixth floor of a tower (approximately 200 ft high) looking out of 

the windows towards the target site, which was at ~0.5 km in range and consisted of two military 
5 

vehicles and natural backgrounds, including grass, brush, and trees (figures 4 and 5). In addition 

to the 200-ft elevation of the sixth floor of the tower, the tower, itself, was situated on top of a 

ridge ~175 ft above the target site. 

Figure 4. Precision Armaments Laboratory tower with elevator 

that housed the polarimetric sensor situated on the sixth floor.
6 

Figure 5. Target site consisting of two military vehicles and a natural background. 

The test was conducted on May 13, 2009, but this image was taken in the 

preceding fall. Therefore, during the test, the grass was alive and thick, 

and the bushes and trees contained leaves.

Environmental measurements available at the target site include air temperature, relative 

humidity, ceilometer data, and pyrgeometer (precision infrared radiometer [PIR]) data. The 

ceilometer provides real-time reports of cloud bases and depths directly above the ceilometer, 

and determines cloud cover by using a weighted average of 30-s cloud hit reports over a 30-min 

period. The pyrgeometer measured ambient LWIR radiation from 3–50 μm within a 2π steradian 

FOV. 

The data acquisition clocks for the environmental data and the camera were synced to ensure 

coincident data. The temporal resolutions of the data are as follows: air temperature, relative 

humidity and pyrgeometer—2 s; ceilometer—10 s; and camera—10 min. Data were acquired 

continuously between 00:00 and 23:00 on May 13, 2009. 

2.4 Image Analysis 

A contrast-based study was performed between the military vehicles and their immediate 

backgrounds. A contrast-based study was also performed between a target (surrogate tank) and 

its immediate backgrounds. Data for the target directly facing the tower in figure 5 is used in the 

analysis. The exact scene used in the analysis is shown in figure 6 and consists of the surrogate 

tank and the surrounding grass and trees/brush. This target was selected because most of its 

surfaces are oriented in the same direction relative to the FOV of the camera. Therefore, widely 

varying magnitudes of polarimetric signatures due to diversity of surface geometry minimally 

affect the target’s mean signatures. 
7 

Figure 6. The test target and its natural background. 

The target, grass and trees regions of interest 

correspond to the blue, red and green boxes, 

respectively. 

The data products used in this study include S0 and S1, where S0 is the total intensity (equivalent 

to conventional thermal image), and S1 is the horizontal minus the vertical components of 

polarization. The S2 Stokes parameter (+45° minus –45° polarized components) and degree of 

linear polarization are excluded because the positive 45° quadrant of the MidIR sensor was not 

functioning properly, and so these data were not available for comparison with the corresponding 

LWIR parameters. Because S0 and S1 are of different magnitudes, the analysis was performed 

on standardized versions of these images (6, 7). Specifically, each image had its mean subtracted 

and was normalized by its standard deviation. This made it possible to directly compare the 

contrasts for both the S0 and S1 images. Using temporal sequences of co-registered images, 

regions of interest were defined for the target and its backgrounds, and the mean values were 

calculated for both data products at each time in the series. The contrast is defined as the 

absolute value of the difference between the mean target value, ߤ́

௧ , and the mean background 

́ߤ ,value

௕, where the prime indicates that the means were calculated using standardized images: 

contrast ൌ  |ߤ́

௧ െ ߤ́௕|. (1) 

Because standardizing the images gives them unitless values, the contrast defined by equation 1 

is also unitless. 

Examples of contrast values calculated using equation 1 and their corresponding images are 

shown in figure 7. The contrasts were calculated for the LWIR S0 images of the scene in figure 

6, taken at three different times of the day. Because this scene has two different natural 

backgrounds, one is chosen at a time to calculate the contrast between the target and the chosen 

background. In the case of figure 7, the grass background is used to calculate the contrast. 
8 

Figure 7. Example contrast values comparing the target to the grass and the 

corresponding S0 image taken at a. 07:00, b. 11:00, and c. 19:00.

3. Results 

The results are presented in the form of two different types of plots. The first is diurnal plots of 

standardized S0 and S1, which allow for a more direct comparison between the MidIR and LWIR 

data, as well as between S0 and S1 for each waveband. It must be remembered, though, that the 

standardized data are unitless. In general, S0 magnitudes are greater than S1 magnitudes because 

light from the scene must be filtered out in order to obtain the S1 image. In addition, LWIR 

signatures are generally stronger than MidIR signatures due to the efficiency at which ambient 

objects emit in the LWIR as opposed to the MidIR. The second type of plot is diurnal contrast 

plots calculated using equation 1. Included with each of these plots are the corresponding 

environmental data. The ceilometer data are omitted because the cloud information can be 

obtained from the pyrgeometer (PIR) data. A direct comparison of ceilometer and pyrgeometer 

data revealed that the baseline reading for a cloudless daytime sky was roughly 275–280 W/m2. 

Any value higher than this typically indicates the presence of clouds such that the higher the 

value, the thicker the cloud cover. During this study, sunrise and sunset occurred at roughly 

05:00 and 20:00, respectively. 

3.1 Diurnal Standardized S0 and S1 

Figures 8 presents the MidIR and LWIR standardized diurnal plots of S0 values for the regions of 

interest defined in figure 6 corresponding to the surrogate tank, grass, and trees. The missing 

MidIR data corresponds to periods in which non-uniformity corrections were performed. As 

expected, the S0 values for the regions of interest mirror each other in both wavebands, although 

the use of standardized data masks the fact that the S0 magnitudes in the LWIR were larger than 

in the MidIR. The S0 values in the LWIR were on the order of 10–3 W/cm2

-sr, while in the 

MidIR, they were on the order of 10–4 W/cm2

-sr. Notice that between 06:00 and 08:00, the S0

for the grass and trees in both wavebands has a shorter lag time after the increase in air 
9 

temperature than the tank does. This is because the grass and leaves of the trees have low mass 

and, therefore, follow air temperature more rapidly than the tank. These details determine the 

temporal occurrence of thermal crossover periods between the tank and its background. 

Figure 8. Diurnal plots of standardized S0 values in the MidIR and LWIR for surrogate tank (blue), grass (red), and 

trees (green) regions of interest. 

Figures 9 shows the MidIR and LWIR standardized diurnal plots of S1 values for the test scene. 

The LWIR S1 profiles for the grass and trees do not vary much, and the magnitude of the S1

values for the tank is consistently larger than for the grass and trees. The S1 values for the tank 

are negative which, given the geometry of the experimental setup, implies that the dominant 

component of the S1 signature is due to emission. The variance in the S1 curve for the tank is 

due to the presence of clouds that have moved into the area as the day progressed. The result is a 

decrease in the magnitude of S1 for the tank. The clouds affect the scene in two ways: first, they 

decrease the amount of solar energy that reach the objects in the scene and, therefore, decrease 

the rate at which these objects are heated; and second, they act as additional sources of IR light 

because they radiate IR light as well as reflect the IR light emitted from the Earth back down 

onto the scene. This additional IR light is then reflected off of the more reflective objects in the 

scene (in this case, the tank) and becomes partially polarized (8, 9). This reflected component of 

polarization is oriented at 90° to and competes with the emitted component and effectively 

reduces the overall magnitude of the LWIR polarimetric signature of the tank. 
10 

Figure 9. Diurnal plots of standardized S1 values in the MidIR and LWIR for surrogate tank (blue), grass (red), and 

trees (green) regions of interest.

Before sunrise, the MidIR S1 signatures were very stable with the tank, having values slightly 

higher than the background. When the sun rose, the objects in the scene began to absorb photons 

and heat up. Between 06:00 and 09:00, this resulted in a crossover into an increasingly negative 

S1 regime for the tank, suggesting that the dominant component of polarization is emission. 

After 09:00, this process reversed and the tank’s MidIR S1 signature experienced another 

crossover and remained positive for the remainder of the day. This positive S1 magnitude was 

directly correlated with the presence of clouds in the sky. These observations are consistent with 

the clouds acting as a source of MidIR optical background that produced a reflected component 

greater than the emitted component (10). 

3.2 Diurnal Contrast 

Figures 10 and 11 show the diurnal contrasts between the tank and its natural background (grass 

and trees, respectively) in the LWIR S0 and S1 and MidIR S1. The MidIR S0 contrast is omitted 

because it is very similar to the contrast in the LWIR S0. For the majority of the day, the contrast 

in LWIR S1 is higher than in LWIR S0 or MidIR S1 and is reduced by the presence of clouds, 

which act as sources of LWIR optical background radiation. The peak in MidIR S1 contrast 

between 08:00 and 10:00 is due to polarized emission resulting from the heating of the tank. As 

clouds begin to enter the atmosphere at 10:00, the tank’s MidIR S1 signature begins to acquire a 

larger reflective component, resulting in the crossover at approximately 10:30 and the 

subsequent contrast modulation throughout the rest of the day. The anti-correlation with the 

presence of clouds between the tank’s LWIR and MidIR S1 contrast is most readily observed 

between 12:00 and 16:00. Peaks in cloud cover at 13:00 and 14:30 are associated with decreases 
11 

in LWIR S1 contrast and improvements in MidIR S1 contrast, while during the period of 

relatively clear skies between 15:00 and 16:00, the LWIR S1 contrast is at its maximum during 

the 24-h period and the MidIR S1 contrast falls to zero. 

The contrasts between the tank and the trees (figure 11) are similar to that between the tank and 

the grass with a few exceptions. The improved contrast between the tank and the trees in the 

LWIR S1 was consistently greater during the periods 00:00 to 10:00 and 20:00 to 22:00 than 

between the tank and the grass. The two thermal crossovers between the tank and the trees 

occurred at 08:00 and 20:30. The MidIR S1 contrast between the tank and trees is very similar to 

the case between the tank and the grass. Most importantly, the inverse correlation of the 

relationship of LWIR S1 and MidIR S1 to the presence of clouds remains between the tank and 

trees. 

Figure 10. Diurnal contrast between the tank and its background of grass on May 13, 2009. 
12 

Figure 11. Diurnal contrast between the tank and its background of trees on May 13, 2009. 

4. Conclusions 

In this study, the temporal occurrence of conventional thermal and polarimetric inversions was 

examined, as well as their correlations to environmental factors. Imagery was recorded with two 

polarimetric IR sensors. The first was a LWIR sensor employing a 324×256 microbolometer 

array using a spinning achromatic retarder to perform the polarimetric filtering. The second was 

a MidIR polarimetric sensor based on a DOA approach with a 640×512 indium antimonide 

(InSb) FPA. The images used in this study included the S0 and S1 images of a scene containing a 

military vehicle and the natural background. In addition, relevant meteorological parameters 

measured during the test periods included air temperature, ambient loading in the LWIR, relative 

humidity, cloud cover, height, and density. 

This study revealed that during most thermal inversion periods, a polarimetric contrast remained 

between at least some facet of the target—and in many cases, the whole target—and its 

background. In addition, the data showed that the chief factors affecting polarimetric contrast 

were the amount of thermal emission from the objects in the scene and the abundance of MidIR 

and LWIR sources in the optical background. 

Furthermore, it was observed that the optical background due to cloud cover decreases LWIR S1

contrast, while it increases MidIR S1 contrast. This is consistent with the notion that MidIR 

polarimetric signatures tend to have a higher reflection component than LWIR polarimetric 

signatures. 
13 

Typical thermal inversions can affect contrast for up to 2 h at a time, reducing the effectiveness 

of thermal imaging systems and jeopardizing the success of military and security missions. The 

findings of this study suggest that conventional thermal imagery can be enhanced by 

incorporating fused MidIR and LWIR polarimetric information. The waveband that showed the 

most promise for polarimetrically enhancing conventional thermal imaging during this test was 

LWIR. The ability of LWIR polarimetric imaging to enhance conventional thermal imaging is 

limited by its susceptibility to the optical background. If a polarimetrically enhanced LWIR 

thermal imager is being used during a mission under conditions in which there are significant 

optical background sources, then the performance of the system will reduce to that of a 

conventional thermal system. By fusing LWIR and MidIR polarimetric data, it may be possible 

to extend the polarimetric enhancement of conventional thermal imagery into the periods of high 

optical background by exploiting the reflective nature of MidIR polarimetric signatures. 

 
14 

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Infrared Radiometers. App. Optics 1999, 38 (15), 3157–3165. 

 
15 

List of Symbols, Abbreviations, and Acronyms 

ARL U.S. Army Research Laboratory 

CO2 carbon dioxide 

DOA division-of-aperture 

FOV field of view 

FPA focal plane array 

H2O water 

I

2 image intensification 

InSb indium antimonied 

LWIR long-wave IR 

MidIR mid-wave IR 

PIR precision infrared radiometer 
16 

No. of 

Copies Organization 

 1 ADMNSTR 

 ELECT DEFNS TECHL INFO CTR 

 ATTN DTIC OCP 

 8725 JOHN J KINGMAN RD STE 0944 

 FT BELVOIR VA 22060-6218 

 1 CD OFC OF THE SECY OF DEFNS 

 ATTN ODDRE (R&AT) 

 THE PENTAGON 

 WASHINGTON DC 20301-3080 

 1 US ARMY RSRCH DEV AND ENGRG 

 CMND 

 ARMAMENT RSRCH DEV & ENGRG 

 CTR 

 ARMAMENT ENGRG & TECHNLGY 

 CTR 

 ATTN AMSRD AAR AEF T J MATTS 

 BLDG 305 

 ABERDEEN PROVING GROUND MD 

 21005-5001 

 1 PM TIMS, PROFILER (MMS-P) 

 AN/TMQ-52 

 ATTN B GRIFFIES 

 BUILDING 563 

 FT MONMOUTH NJ 07703 

 1 US ARMY ABERDEEN TEST CENTER 

 ATTN TEDT AT WFT F CARLEN 

 400 COLLERAN ROAD 

 ABERDEEN PROVING GROUND MD 

 21005-5009 

 1 US ARMY ARMAMENT RSRCH AND 

 DEVELOPMENT ENGINEERING CTR 

 ATTN AMSRD AAR MEF S L E ROTH 

 BLDG 407 

 PICATINNY ARSENAL NJ 07806-5000 

 1 US ARMY CECOM RDEC NVESD 

 ATTN AMSRD CER NV ST SIP 

 J HOWE 

 10221 BURBECK RD STE 430 

 FT BELVOIR VA 22060-5806 

 1 US ARMY INFO SYS ENGRG CMND 

 ATTN AMSEL IE TD A RIVERA 

 FT HUACHUCA AZ 85613-5300 

No. of 

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 1 COMMANDER 

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 ATTN AMSRD AMR 

 W C MCCORKLE 

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 REDSTONE ARSENAL AL 35898-5000 

 1 US ARMY RDECOM ARDEC 

 ATTN M WOOLLEY 

 BLDG 407 

 PICATINNY ARSENAL NJ 07806 

 1 US ARMY RDECOM ARDEC 

 ATTN AMSRD AAR AEP S 

 J ROMANO 

 BLDG 407 

 PICATINNY ARSENAL NJ 07806-5000 

 1 US ARMY TARDEC 

 ATTN AMSRD TAR MS 263 

 G GRANT 

 6501 EAST 11 MILE RD 

 WARREN MI 48397-5000 

 1 AFRL/RYJT 

 ATTN R T MACK 

 2241 AVIONICS CIRCLE BLDG 620 

 WRIGHT-PATTERSON AFB OH 

 45433-7320 

 1 AFRL/VS 

 ATTN T R CAUDILL 

 3550 ABERDEEN AVE SE BLDG 423 

 KIRTLAND AFB NM 87117 

 1 AFRL/VSS 

 ATTN M J DUGGIN 

 3550 ABERDEEN AVE SE 

 KIRTLAND AFB NM 87117 

 1 USAFRL-VSSS 

 ATTN M FETROW 

 3550 ABERDEEN SE 

 KIRTLAND AFB NM 87117 

 1 US GOVERNMENT PRINT OFF 

 DEPOSITORY RECEIVING SECTION 

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17 

No. of 

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 1 JOHNS HOPKINS UNIVERSITY 

 APPLIED PHYSICS LAB 

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 1 COLLEGE OF OPTICAL SCIENCES 

 UNIVERSITY OF ARIZONA 

 ATTN B M RATLIFF 

 TUCSON AR 85721 

 1 UNIVERSITY OF ARIZONA 

 COLLEGE OF OPTICAL SENSORS 

 ATTN S TYO 

 TUCSON AZ 85721 

 1 GEORGIA TECH RSRCH INSTITUTE 

 ATTN J S ACCETTA 

 2015 YALE BLVD SE 

 ALBUQUERQUE NM 87106 

 1 MONTANA STATE UNIVERSITY 

 ATTN J SHAW 

 108 CULBERTSON HALL 

 P.O. BOX 172000 

 BOZEMAN MT 59717-2000 

 2 POLARIS SENSOR TECHNOLOGIES 

 INC 

 ATTN D B CHENAULT 

 ATTN J L PEZZANITI 

 200 WESTSIDE SQUARE STE 320 

 HUNTSVILLE AL 35801 

 1 US ARMY RSRCH LAB 

 ATTN RDRL CIM G T LANDFRIED 

 BLDG 4600 

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 21005-5066 

 1 DIRECTOR 

 US ARMY RSRCH LAB 

 ATTN RDRL ROE V W D BACH 

 PO BOX 12211 

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 27709 

No. of 

Copies Organization 

 15 US ARMY RSRCH LAB 

 ATTN IMNE ALC HRR MAIL & 

 RECORDS MGMT 

 ATTN RDRL CIE S K GURTON 

 (5 COPIES) 

 ATTN RDRL CIE S M FELTON 

 (5 COPIES) 

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 ATTN RDRL SEE E K KLETT, JR. 

 ATTN RDRL SES E D ROSARIO 

 ADELPHI MD 20783-1197 

TOTAL: 41 (1 ELEC, 1 CD, 39 HCS)
18 

INTENTIONALLY LEFT BLANK.